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The Top 20 Technology Blunders

July 20, 2018  |  Posted By: Pete Ferguson

AKF Technical Due Diligence Top Mistakes

One of the most common questions we get is “What are the most common failures you see tech and product teams make?” To answer that question we queried our database consisting of 11 years of anonymous client recommendations. Here are the top 20 most repeated failures and recommendations:

1) Failing to Design for Rollback
If you are developing a SaaS platform and you can only make one change to your current process make it so that you can always roll back any of your code changes. Yes, we know that it takes additional engineering work and additional testing to make nearly any change backwards compatible but in our experience that work has the greatest ROI of any work you can do. It only takes one really bad release in which your site performance is significantly degraded for several hours or even days while you attempt to “fix forward” for you to agree this is of the utmost importance. The one thing that is most likely to give you an opportunity to find other work (i.e. “get fired”) is to roll a product that destroys your business. In other words, if you are new to your job DO THIS BEFORE ANYTHING ELSE; if you have been in your job for awhile and have not done this DO THIS TOMORROW. (Related Content: Monitoring for Improved Fault Detection)

2) Confusing Product Release with Product Success
Do you have “release” parties? Stop it! You are sending your team the wrong message! A release has nothing to do with creating shareholder value and very often it is not even the end of your work with a specific product offering or set of features. Align your celebrations with achieving specific business objectives like a release increasing signups by 10%, or increasing checkouts by 15% or increasing the average sale price of a all checkouts by 12% or increasing click-through-rates by 22%. See #10 below on incenting a culture of excellence. Don’t celebrate the cessation of work – celebrate achieving the success that makes shareholder’s wealthy! (Related Content: Agile and the Cone of Uncertainty)

3) Insular Product Development / Engineering
How often does one of your engineering teams complain about not “being in the loop” or “being surprised” by a change? Does your operations team get surprised about some new feature and its associated load on a database? Does engineering get surprised by some new firewall or routing infrastructure resulting in dropped connections? Do not let your teams design in a vacuum and “throw things over the wall” to another group. Organize around your outcomes and “what you produce” in cross functional teams rather than around activities and “how you work.” (Related Content: The No Surprises Rule)

4) Over Engineering the Solution
One of our favorite company mottos is “simple solutions to complex problems”. The simpler the solution, the lower the cost and the faster the time to market. If you get blank stares from peers or within your organization when you explain a design do not assume that you have a team of idiots – assume that you have made the solution overly complex and ask for assistance in resolving the complexity.




Image Source: Hackernoon.com


5) Allowing History to Repeat itself
Organizations do not spend enough time looking at past failures. In the engineering world, a failure to look back into the past and find the most commonly repeated mistakes is a failure to maximize the value of the team. In the operations world, a failure to correlate past site incidents and find thematically related root causes is a guarantee to continue to fight the same fires over and over. The best and easiest way to improve our future performance is to track our past failures, group them into groups of causation and treat the root cause rather than the symptoms. Keep incident logs and review them monthly and quarterly for repeating issues and improve your performance. Perform post mortems of projects and site incidents and review them quarterly for themes.

6) Vendor Lock
Every vendor has a quick fix for your scale issues. If you are a hyper growth SaaS site, however, you do not want to be locked into a vendor for your future business viability; rather you want to make sure that the scalability of your site is a core competency and that it is built into your architecture. This is not to say that after you design your system to scale horizontally that you will not rely upon some technology to help you; rather, once you define how you can horizontally scale you want to be able to use any of a number of different commodity systems to meet your needs. As an example, most popular databases (and NoSQL solutions) provide for multiple types of native replication to keep hosts in synch.

7) Relying on QA to Find Your Mistakes
You cannot test quality into a system and it is mathematically impossible to test all possibilities within complex systems to guarantee the correctness of a platform or feature. QA is a risk mitigation function and it should be treated as such. Defects are an engineering problem and that is where the problem should be treated. If you are finding a large number of bugs in QA, do not reward QA – figure out how to fix the problem in engineering! Consider implementing test driven design as part of your PDLC. If you find problems in production, do not punish QA; figure out how you created them in engineering. All of this is not to say that QA should not be held responsible for helping to mitigate risk – they should – but your quality problems are an engineering issue and should be treated within engineering.

8) Revolutionary or “Big Bang” Fixes
In our experience, complete re-writes or re-architecture efforts end up somewhere on the spectrum of not returning the desired ROI to complete and disastrous failures. The best projects we have seen with the greatest returns have been evolutionary rather than revolutionary in design. That is not to say that your end vision should not be to end up in a place significantly different from where you are now, but rather that the path to get there should not include “and then we turn off version 1.0 and completely cutover to version 2.0”. Go ahead and paint that vivid description of the ideal future, but approach it as a series of small (but potentially rapid) steps to get to that future. And if you do not have architects who can help paint that roadmap from here to there, go find some new architects.

9) The Multiplicative Effect of Failure – Eliminate Synchronous Calls
Every time you have one service call another service in a synchronous fashion you are lowering your theoretical availability. If each of your services are designed to be 99.999% available, where a service is a database, application server, application, webserver, etc. then the product of all of the service calls is your theoretical availability. Five calls is (.99999)^5 or 99.995 availability. Eliminate synchronous calls wherever possible and create fault-isolative architectures to help you identify problems quickly.

10) Failing to Create and Incentivize a Culture of Excellence
Bring in the right people and hold them to high standards. You will never know what your team can do unless you find out how far they can go. Set aggressive yet achievable goals and motivate them with your vision. Understand that people make mistakes and that we will all ultimately fail somewhere, but expect that no failure will happen twice. If you do not expect excellence and lead by example, you will get less than excellence and you will fail in your mission of maximizing shareholder wealth. (Related Content: Three Reasons Your Software Engineers May Not Be Successful)

AKF Tech Due Diligence Growth Blog Failure

11) Under-Engineer for Scale
The time to think about scale is when you are first developing your platform. If you did not do it then, the time to think about scaling for the future is right now! That is not to say that you have to implement everything on the day you launch, but that you should have thought about how it is that you are going to scale your application services and your database services. You should have made conscious decisions about tradeoffs between speed to market and scalability and you should have ensured that the code will not preclude any of the concepts we have discussed in our scalability postings. Hold quarterly scalability meetings where you discuss what you need to do to scale to 10x your current volume and create projects out of the action items. Approach your scale needs in evolutionary rather than revolutionary fashion as in #8 above.

12) “Not Built Here” Culture
We see this all the time. You may even have agreed with point (6) above because you have a “we are the smartest people in the world and we must build it ourselves” culture. The point of relying upon third parties to scale was not meant as an excuse to build everything yourselves. The real point to be made is that you have to focus on your core competencies and not dilute your engineering efforts with things that other companies or open source providers can do better than you. Unless you are building databases as a business, you are probably not the best database builder. And if you are not the best database builder, you have no business building your own databases for your SaaS platform. Focus on what you should be the best at: building functionality that maximizes your shareholder wealth and scaling your platform. Let other companies focus on the other things you need like routers, operating systems, application servers, databases, firewalls, load balancers and the like.

13) A New PDLC will Fix My Problems
Too often CTO’s see repeated problems in their product development life cycles such as missing dates or dissatisfied customers and blame the PDLC itself.

The real problem, regardless of the lifecycle you use, is likely one of commitment and measurement. For instance, in most Agile lifecycles there needs to be consistent involvement from the business or product owner. A lack of involvement leads to misunderstandings and delayed products. Another very common problem is an incomplete understanding or training on the existing PDLC. Everyone in the organization should have a working knowledge of the entire process and how their roles fit within it. Most often, the biggest problem within a PDLC is the lack of progress measurement to help understand likely dates and the lack of an appropriate “product discovery” phase to meet customer needs. (Related Content: The Top Five Most Common PDLC Failures)

14) Inability to Hire Great People Quickly
Often when growing an engineering team quickly the engineering managers will push back on hiring plans and state that they cannot possibly find, interview, and hire engineers that meet their high standards. We agree that hiring great people takes time and hiring decisions are some of the most important decisions managers can make. A poor hiring decision takes a lot of energy and time to fix. However, there are lots of ways to streamline the hiring process in order to recruit, interview, and make offers very quickly. A useful idea that we have seen work well in the past are interview days, where potential candidates are all invited on the same day. This should be no more than 2 - 3 weeks out from the initial phone screen, so having an interview day per months is a great way to get most of your interviewing in a single day. Because you optimize the interview process people are much more efficient and it is much less disruptive to the daily work that needs to get done the rest of the month. Post interview discussions and hiring decisions should all be made that same day so that candidates get offers or letters of regret quickly; this will increase the likelihood of offers being accepted or make a professional impression on those not getting offers. The key is to start with the right answer that “there is a way to hire great people quickly” and the myriad of ways to make it happen will be generated by a motivated leadership team.


AKF Technical Due Diligence Seed Feed Weed


15) Diminishing or Ignoring SPOFs (Single Point of Failure)
A SPOF is a SPOF and even if the impact to the customer is low it still takes time away from other work to fix right away in the event of a failure. And there will be a failure…because that is what hardware and software does, it works for a long time and then eventually it fails! As you should know by now, it will fail at the most inconvenient time. It will fail when you have just repurposed the host that you were saving for it or it will fail while you are releasing code. Plan for the worst case and have it run on two hosts (we actually recommend to always deploy in pools of three or more hosts) so that when it does fail you can fix it when it is most convenient for you.

16) No Business Continuity Plan
No one expects a disaster but they happen and if you cannot keep up normal operations of the business you will lose revenue and customers that you might never get back. Disasters can be huge, like Hurricane Katrina, where it take weeks or months to relocate and start the business back up in a new location. Disasters can also be small like a winter snow storm that keeps everyone at home for two days or a HAZMAT spill near your office that keeps employees from coming to work. A solid business continuity plan is something that is thought through ahead of time, before you need it, and explains to everyone how they will operate in the event of an emergency. Perhaps your satellite office will pick up customer questions or your tech team will open up an IRC channel to centralize communication for everyone capable of working remotely. Do you have enough remote connections through your VPN server to allow for remote work? Spend the time now to think through what and how you will operate in the event of a major or minor disruption of your business operations and document the steps necessary for recovery.

17) No Disaster Recovery Plan
Even worse, in our opinion, than not having a BC plan is not having a disaster recovery plan. If your company is a SaaS-based company, the site and services provided is the company’s sole source of revenue! Moreover, with a SaaS company, you hold all the data for your customers that allow them to operate. When you are down they are more than likely seriously impaired in attempting to conduct their own business. When your collocation facility has a power outage that takes you completely down, think 365 Main datacenter in San Francisco, how many customers of yours will leave and never return? Our preference is to provide your own disaster recovery through multiple collocation facilities but if that is not yet technically feasible nor in the budget, at a minimum you need your code, executables, configurations, loads, and data offsite and an agreement in place for both collocation services as well as hosts. Lots of vendors offer such packages and they should be thought of as necessary business insurance.

If you are cloud hosted, this still applies to you! We often find in technical due diligence reviews that small companies who are rapidly growing haven’t yet initiated a second active tech stack in a different availability zone or with a second cloud provider. Just because AWS, Azure and others have a fairly reliable track record doesn’t mean they always will. You can outsource services, but you still own the liability!


Image Source: Kaibizzen.com.au


18) No Product Management Team or Person
In a similar vein to #13 above, there needs to be someone or a team of people in the organization who have responsibility for the product lines. They need to have authority to make decisions about what features get added, which get delayed, and which get deprecated (yes, we know, nothing ever gets deprecated but we can always hope!). Ideally these people have ownership of business goals (see #10) so they feel the pressure to make great business decisions.

19) Failing to Implement Continuously
Just because you call it scheduled maintenance does not mean that it does not count against your uptime. While some of your customers might be willing to endure the frustration of having the site down when they want to access it in order to get some new features, most care much more about the site being available when they want it. They are on the site because the existing features serve some purpose for them; they are not there in the hopes that you will rollout a certain feature that they have been waiting on. They might want new features, but they rely on existing features. There are ways to roll code, even with database changes, without bringing the site down (back to #17 - multiple active sites also allows for continuous implementation and the ability to roll back). It is important to put these techniques and processes in place so that you plan for 100% availability instead of planning for much less because of planned down time.

20) Firewalls, Firewalls, Everywhere!
We often see technology teams that have put all public facing services behind firewalls while many go so far as to put firewalls between every tier of the application. Security is important because there are always people trying to do malicious things to your site, whether through directed attacks or random scripts port scanning your site. However, security needs to be balanced with the increased cost as well as the degradation in performance. It has been our experience that too often tech teams throw up firewalls instead of doing the real analysis to determine how they can mitigate risk in other ways such as through the use of ACLs and LAN segmentation. You as the CTO ultimately have to make the decision about what are the best risks and benefits for your site.


AKF Technical Due Diligence

Whatever you do, don’t make the mistakes above! AKF Partners helps companies avoid costly product and technology mistakes - and we’ve seen most of them.  Give us a call or shoot us an email.  We’d love to help you achieve the success you desire.

 

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People Due Diligence

July 12, 2018  |  Posted By: Robin McGlothin

Most companies do a thorough job of financial due diligence when they acquire other companies. But all too often, dealmakers simply miss or underestimate the significance of people issues. The consequences can be severe, from talent loss after a deal’s announcement, to friction or paralysis caused by differences in decision-making styles.

When acquirers do their people homework, they can uncover skills & capability gaps, points of friction, and differences in decision making. They can also make the critical people decisions - who stays, who goes, who runs the various lines of business, what to do with the rank and file at the time the deal is announced or shortly thereafter. Making such decisions within the first 90 days is critical to the success of a deal.

Take for example, Charles Schwab’s 2000 acquisition of US Trust.  Schwab & the nation’s oldest trust company set out to sign up the newly minted millionaires created by a soaring bull market.  But the cultures could not have been farther apart – a discount do-it-yourself stock brokerage style and a full-service provider devoted to pampering multimillionaires can make for a difficult integration.  Six years after the merger, Chuck Schwab came out of retirement to fix the issues related to culture clash. The acquisition reflects a textbook common business problem. The dealmakers simply ignored or underestimated the significance of people and cultural issues.

Another example can be found in the 2002 acquisition of PayPal by eBay.  The fact that many on the PayPal side referred to it as a merger, sets the stage for conflicting cultures.  eBay was often embarrassed by the fact that PayPal invoice emails for a won auction arrived before the eBay end of auction email - PayPal made eBay look bad in this instance and the technology teams were not eager to combine.  As well, PayPal titles were discovered to be one level higher than eBay titles considering the scope of responsibilities.  Combining the technology teams did not go well and was ultimately scrapped in favor of dual teams - not the most efficient organizational model.

People due diligence lays the groundwork for a smooth integration. Done early enough, it also helps acquirers decide whether to embrace or kill a deal and determine the price they are willing to pay.  There’s a certain amount of people due diligence that companies can and must do to reduce the inevitable fallout from the acquisition process and smooth the integration.

Ultimately, the success or failure of any deal has to do with people.  Empowering people and putting them in a position where they will be successful is part of our diligence evaluation at AKF Partners. In our experience with clients, an acquiring company must start with some fundamental question:

1. What is the purpose of the deal?
2. Whose culture will the new organization adopt?
3. Will the two cultures mesh?
4. What organizational structure should be adopted?
5. How will rank-and-file employees react to the deal?

Once those questions are answered, people due diligence can focus on determining how well the target’s current structure and culture will mesh with those of the proposed new company, who should be retained and by what means, and how to manage the reaction of the employee base.

In public, deal-making executives routinely speak of acquisitions as “mergers of equals.” That’s diplomatic, politically correct speak and usually not true. In most deals, there is not only a financial acquirer, there is also a cultural acquirer, who will set the tone for the new organization after the deal is done. Often, they are one and the same, but they don’t have to be.

During our Technology Due Diligence process at AKF Partners, we evaluate the product, technology and support organizations with a focus on culture and think through how the two companies and teams are going to come together.  Who the cultural acquirer is dependes on the fundamental goal of the acquisition. If the objective is to strengthen the existing product lines by gaining customers and achieving economies of scale, then the financial acquirer normally assumes the role of the cultural acquirer.

People due diligence, therefore, will be to verify that the target’s culture is compatible enough with the acquirers to allow for the building of necessary bridges between the two organizations.  Key steps that are often missed in the process:

• Decide how the two companies will operate after the acquisition — combined either as a fully integrated operating company or as autonomous operating companies.
• Determine the new organizational structure and identify areas that will need to be integrated.
• Decide on the new executive leadership team and other key management positions.
• Develop the process for making employment-related decisions.

With regard to the last bullet point, some turnover is to be expected in any company merger. Sometimes shedding employees is even planned. It is important to execute The Weed, Seed & Feed methodology ongoing not just at acquisition time.  Unplanned, significant levels of turnover negatively impact a merger’s success.



AKF Partners brings decades of hands-on executive operational experience, years of primary research, and over a decade of successful consulting experience to the realm of product organization structure, due diligence and technology evaluation.  We can help your company successfully navigate the people due diligence process. 


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Monitoring the Good, the Bad, the Ugly for Improved Fault Detection

July 8, 2018  |  Posted By: Robin McGlothin

AKF often recommends to our clients the adoption of business metric monitoring – the use of high-level user activity or transaction patterns that can often provide early warning of an incident.  Business metric monitors will not tell you where or what the problem is, rather – and most importantly – they tell you something appears to be abnormal and should be investigated, that something has affected your customer experience.




A significant part of recovery time (and therefore availability) is the time required to detect and localize service incidents.  A 2013 study by Business Internet Group of San Francisco found that of the 40 top-performing websites (as identified by KeyNote Systems), 72% had suffered user-visible failures in common functionality, such as items not being added to a shopping cart or an error message being displayed.

Our conversations with clients confirm that detecting these failures is a significant problem.  AKF Partners estimates that 75% of the time spent recovering from application-level failures is time spent detecting them!  Application-level failures can sometimes take days to detect, though they are repaired quickly once found.  Fast detection of these failures (Time to Detect – TTD) is, therefore, a key problem in improving service availability.
 
                The duration of a product impairment is TTR.

To improve TTR, implement a good notification system that first, based on business metrics, tells you that an error affecting your users is happening.  Then, rely upon application and system monitoring to inform you on where and what has failed.  Make sure to have good and easy view logs for all errors, warnings and other critical data your application creates.  We already have many technologies in this space and we just need to employ them in an effective manner with the focus on safeguarding the client experience.

In the form of Statistical Process Control (SPC – defined below) two relatively simple methods to improve TTD:

  1. Business KPI Monitors (Monitor Real User Behavior): Passively monitor critical user transactions such as logins, queries, reports, etc.  Use math to determine abnormal behavior.  This is the first line of defense.
  2. Synthetic Transactions (Simulate User Behavior):  Synthetic transactions are scripted actions that attempt to mimic real customer behavior. Examples might be sign-ons, add to cart, etc. They provide a more meaningful view of your customers’ experiences vs. just looking at page load times, error rates, and similar. Do this with Keynote or a similar product and expand it to an internal systems scope.  Alerts from a passive monitor can be confirmed or denied and escalated as appropriate.  This is the second line of defense.

Monitor the Bad – potential, & actual bad things (alert before they happen), and tune and continuously improve (Iterate!) 

If you can’t identify all problem areas, identify as many as possible.  The best monitoring starts before there’s a problem and extends beyond the crisis.
Because once the crisis hits, that’s when things get ugly!  That’s when things start falling apart and people point fingers.



At times, failures do not disable the whole site, but instead cause brown-outs, where part of a site’s functionality is disabled or only some users are unable to access the site.  Many of these failures are application-level failures that change the user-visible functionality of a service but do not cause obvious lower-level failures detectable by service operators.  Effective monitoring will detect these faults as well. 



The more proactive you can be about identifying the issues, the easier it will be to resolve and prevent them.

In fault detection, the aim is to determine whether an abnormal event happened or when an application being monitored is out of control.  The early detection of a fault condition is important in avoiding quality issues or system breakdown, and this can be achieved through the proper design of effective statistical process control with upper & lower limits identified.  If the values of the monitoring statistics exceed the control limits of the corresponding statistics, a fault is detected.  Once a fault condition has been positively detected, the next step is to determine the root cause of the out-of-control status.


One downside of the SPC method is that significant changes in amplitude (natural increases in your business metrics) can cause problems.  An alternative to SPC is First and Second Derivative testing.  These tests tell if the actual and expected curve forms are the same.



Here’s a real-world example of where business metrics help us determine changes in normal usage at eBay. 

We had near real-time graphs of user metrics such as bids, listings, logins, and new user registrations.  The data was graphed week over week.  Usage patterns throughout a day followed a readily identifiable pattern with peaks and valleys.  These graphs were displayed in the Network Operations Center, which was staffed 24x7.  Deviations from the previous week’s pattern had proven useful, identifying issues such as ISP instability in the EU impacting customers trying to access eBay.

Everything seemed normal on a Wednesday evening – right up to the point that bids and listings both took a nosedive.  The NOC quickly initiated the SEV1 process and technical resources checked their areas.  The site had no identifiable faults, services were confirmed to be working fine, yet the user activity was still markedly lower.  Roughly 20 minutes into the SEV1 process, the root cause was identified.  The finale episode of American Idol was being broadcast.  Our site was fine – but our customers had other things on their mind.  The business metric monitors worked – they gave warning of an aberrant usage pattern.

How would your company react to this critical change in normal usage patterns?  Use business metric monitors to detect workload shifts.


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Agile and Dealing With The Cone of Uncertainty

July 8, 2018  |  Posted By: Dave Berardi

The Leap of Faith

When we embark on building SaaS product that will delight customers we are taking a leap of faith. We often don’t even know whether or not the outcomes targeted are possible. Investing and building software is often risky for several reasons:

  • We don’t know what the market wants.
  • The market is changing around us.
  • Competition is always improving their time to market (TTM) releasing competitive products and services.

We have to assume there will be project assumptions made that will be wrong and that the underlying development technology we use to build products is constantly changing and evolving. One thing is clear on the SaaS journey – the future is always murky!

The journey that’s plagued with uncertainty for developing SaaS is seen throughout the industry and is evidenced by success and failure from big and small companies – from Facebook to Apple to Salesforce to Google. Google is one of many innovating B2C companies that have used the cone of uncertainty to help inform how to go to market and whether or not to sunset a service. The company realizes that in addition to innovating, they need to reduce uncertainty quickly.

For example, Google Notebook, a browser-based note-taking and information sharing service, was killed and resurrected as part of Google Docs and has a mobile derivative called Keep. Google Buzz, Google’s first attempt at a social network was quickly killed after a little over a year in 2011. These are just a few B2C examples from Google.  All of these are examples of investments that faced the cone of uncertainty. Predicting successful outcomes longer term and locking in specifics about a product will only be wasteful and risky.

The cone of uncertainty describes the uncertainty and risk that exist when an investment is made for a software project. The cone depicts the amount of risk and degree of precision for certainty thru the funnel. The further out we try to forecast features, capabilities, and adoption, the more risk and uncertainty we must assume. This is true for what we attempt to define as a product to be delivered and the timing on when we will deliver it to market. Over time, firms must make adjustments to the planned path along the way to capture and embrace changing market needs.

In today’s market we must quickly test our hypothesis and drive innovation to be competitive. An Agile product development life cycle (PDLC) and appropriately aligned organization helps us to do just that. To address the challenge the cone represents, we must understand what an Agile PDLC can do for the firm and what it cannot do for the firm.


Address the Uncertainty of the Cone

When we use an Agile approach, we must fix time and cost for development and delivery of a product but we allow for adjustment and changes to scope to meet fixed dates. The team can extend time later in the project but the committed date to delivery does not change. We also do not add people since Brooks Law teaches us that adding human resources to a late software project only delays it further.  Instead we accelerate our ability to learn with frequent deployments to market resulting in a reduction in uncertainty. Throughout this process, discovery of both what the feature set needs to be for a successful outcome and how something should work is accomplished.

Agile allows for frequent iterations that can keep us close to the market thru data. After a deployment, if our system is designed to be monitored, we can capture rich information that will help to inform future prioritization, new ideas about features and modifications that may be needed to the existing feature set. Agile forces us to frequently estimate and as such produce valuable data for our business. The resulting velocity of our sprints can be used to revise future delivery range forecasts for both what will be delivered and when it will be delivered. Data will also be produced throughout our sprints that will help to identify what may be slowing us down ultimately impacting our time to market. Positive morale will be injected into the tams as results can be observed and felt in the short term.

What agile is not and how we must adjust?

While using an Agile method can help address the cone of uncertainty, it’s not the answer to all challenges. Agile does not help to provide a specific date when a feature or scope will be delivered. Instead we work towards ranges. It also does not improve TTM just because our teams started practicing it. Company philosophies, principles, and rules are not defined through an Agile PDLC. Those are up to the company to define. Once defined the teams can operate within the boundaries to innovate. Part of this boundary definition needs to start at the top. Executives need to paint a vivid picture of the desired outcome that stirs up emotion and can be measurable. The vision is at the opening of the cone. Measurable Key Results that executives define to achieve outcomes allow for teams to innovate making tradeoffs as they progress towards the vision. Agile alone does not empower teams or help to innovate. Outcomes, and Key Results (OKRs) cascaded into our organization coupled with an Agile PDLC can be a great combination that will empower teams giving us a better chance to innovate and achieve desirable time to market. Implementing an OKR framework helps to remove the focus of cranking out code to hit a date and redirects the needed attention on innovation and making tradeoffs to achieve the desired outcome.

Agile does not align well with annual budget cycles. While many times, an annual perspective is required by shareholders, an Agile approach is in conflict with annual budgeting. Since Agile sees changing market demands, frequent budget iterations are needed as teams may request additional funding to go after an opportunity. It’s key that finance leaders embrace the importance of adjusting the budgeting approach to align with an Agile PDLC. Otherwise the conflict created could be destructive and create a barrier to the firms desired outcome.

Applying Agile properly benefits a firm by helping to address the cone and reducing uncertainty, empowering teams to deliver on an outcome, and ultimately become more competitive in the global marketplace. Agile is on the verge of becoming table stakes for companies that want to be world class. And as we described above noting the importance of a different approach to something like budgeting, its not just for software – it’s the entire business.

Let Us Help

AKF has helped many companies of all sizes when transitioning to an organization, redefining PDLC to align with desired speed to market outcomes, and SaaS migrations. All three are closely tied and if done right, can help firms compete more effectively. Contact us for a free consultation. We would love to help!


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Three Reasons Your Software Engineers May Not Be Successful

May 10, 2018  |  Posted By: Pete Ferguson

Three Reasons Your Software Engineers May Not Be Successful

At AKF Partners, we have the unique opportunity to see trends among startups and well-established companies in the dozens of technical due diligence and more in-depth technology assessments we regularly perform, in addition to filling interim leadership roles within organizations.  Because we often talk with a variety of folks from the CEO, investors, business leadership, and technical talent, we get a unique top-to-bottom perspective of an organization.

Three common observations

  • People mostly identify with their job title, not the service they perform.
  • Software Engineers can be siloed in their own code vs. contributing to the greater outcome.
  • CEO’s vision vs. frontline perception of things as they really are.

Job Titles Vs. Services

The programmer who identifies herself as “a search engineer” is likely not going to be as engaged as her counterpart who describes herself as someone who “helps improve our search platform for our customers.”

Shifting focus from a job title to a desired outcome is a best practice from top organizations.  We like to describe this as separating nouns and verbs – “I am a software engineer” focuses on the noun without an action: software engineer instead of “I simplify search” where the focus is on verb of the desired outcome: simplify.  It may seem minor or trivial, but this shift can be a contributing impact on how team members understand their contribution to your overall organization. 

Removing this barrier to the customer puts team members on the front line of accountability to customer needs – and hopefully also the vision and purpose of the company at large.  To instill a customer experience, outcome based approach often requires a reworking of product teams given our experience with successful companies.  Creating a diverse product team (containing members of the Architecture, Product, QA and Service teams for example) that owns the outcomes of what they produce promotes:

  • Motivation
  • Quality
  • Creating products customers love

If you have had experience in a Ford vehicle with the first version of Sync (bluetooth connectivity and onscreen menus) – then you are well aware of the frustration of scrolling through three layers of menus to select “bluetooth audio” ([Menu] -> [OK] -> [OK] -> [Down Arrow]-> [OK] -> [Down Arrow] -> [OK]) each time you get into your car.  The novelty of wireless streaming was a key differentiator when Sync first was introduced – but is now table stakes in the auto industry – and quickly wears off when having to navigate the confusing UI likely designed by product engineers each focused on a specific task but void of designing for a great user experience.  What was missing is someone with the vision and job description: “I design wireless streaming to be seamless and awesome - like a button that says “Bluetooth Audio!!!”

Hire for – and encourage – people who believe and practice “my real job is to make things simple for our customers.”

Avoiding Siloed Approach

Creating great products requires engineers to look outside of their current project specific tasks and focus on creating great customer experiences.  Moving from reactively responding to customer reported problems to proactively identifying issues with service delivery in real time goes well beyond just writing software.  It moves to creating solutions.

Long gone are the “fire and forget” days of writing software, burning to a CD and pushing off tech debt until the next version.  To Millennials, this Waterfall approach is foreign, but unfortunately we still see this mentality engrained in many company cultures.

Today it is all about services.  A release is one of many in a very long evolution of continual improvement and progression.  There isn’t Facebook V1 to be followed by V2 … it is a continual rolling out of upgrades and bug fixes that are done in the background with minimum to no downtime.  Engineers can’t afford to be laggard in their approach to continual evolution, addressing tech debt, and contributing to internal libraries for the greater good.

Ensure your technical team understands and is very closely connected to the evolving customer experience and have skin in the game.  Among your customers, there likely is very little patience with “wait until our next release.”  They expect immediately resolution or they will start shopping the competition.

Translating the Vision of the CEO to the Front Lines

During our our more in-depth technology review engagements we interview many people from different layers of management and different functions within the organization.  This gives us a unique opportunity to see how the vision of the CEO migrates down through layers of management to the front-line programmers who are responsible for translating the vision into reality.

Usually - although not always - the larger the company, the larger the divide between what is being promised to investors/Wall Street and what is understood as the company vision by those who are actually doing the work.  Best practices at larger companies include regular all-hands where the CEO and other leaders share their vision and are held accountable to deliverables and leadership checks that the vision is conveyed in product roadmaps and daily stand up meetings.  When incentive plans focus directly on how well a team and individual understand and produce products to accomplish the company vision, communication gaps close considerably.

Creating and sustaining successful teams requires a diverse mix of individuals with a service mindset.  This is why we stress that Product Teams need to be all inclusive of multiple functions.  Architecture, Product, Service, QA, Customer Service, Sales and others need to be included in stand up meetings and take ownership in the outcome of the product. 

The Dev Team shouldn’t be the garbage disposal for what Sales has promised in the most recent contract or what other teams have ideated without giving much thought to how it will actually be implemented. 

When your team understands the vision of the company - and how customers are interacting with the services of your company - they are in a much better position to implement it into reality.

As a CTO or CIO, it is your responsibility to ensure what is promised to Wall Street, private investors, and customers is translated correctly into the services you ultimately create, improve, and publish.

Conclusions

As we look at new start-ups facing explosive 100-200% year-over-year growth, our question is always “how will the current laser focus vision and culture scale?”  Standardization, good Agile practices, understanding technical debt, and creating a scalable on-boarding and mentoring process all lend to best answers to this question.

When your development teams are each appropriately sized, include good representation of functional groups, each team member identifies with verbs vs. nouns (“I improve search” vs. “I’m a software engineer”), and understand how their efforts tie into company success, your opportunities for success, scalability, and adaptability are maximized.

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Experiencing growing or scaling pains?  AKF is here to help!  We are an industry expert in technology scalability, due diligence, and helping to fill leadership gaps with interim CIO/CTO and other positions in addition to helping you in your search for technical leaders.  Put our 200+ years of combined experience to work for you today!

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Enabling TTM With Contributor Model Teams

May 6, 2018  |  Posted By: Dave Berardi

Enabling TTM With Contributor Model Teams

We often speak about the benefits of aligning agile teams with the system’s architecture.  As Conway’s Law describes, product/solution architectures and organizations cannot be developed in isolation.  (See https://akfpartners.com/growth-blog/conways-law) Agile autonomous teams are able to act more efficiently, with faster time to market (TTM).  Ideally, each team should be able to behave like a startup with the skills and tools needed to iterate until they reach the desired outcome.

Many of our clients are under pressure to achieve both effective TTM and reduce the risk of redundant services that produce the same results. During due diligence, we will sometimes discover redundant services that individual teams develop within their own silo for a TTM benefit.  Rather than competing with priorities and waiting for a shared service team to deliver code, the team will build their own flavor of a common service to get to market faster.

Instead, we recommend a shared service team own common services. In this type of team alignment, the team has a shared service or feature on which other autonomous teams depend. For example, many teams within a product may require email delivery as a feature.  Asking each team to develop and operate its own email capability would be wasteful, resulting in engineers designing redundant functionality leading to cost inefficiencies and unneeded complexity.  Rather than wasting time on duplicative services, we recommend that organizations create a team that would focus on email and be used by other teams.

Teams make requests in the form of stories for product enhancements that are deposited in the shared services team’s backlog. (email in this case) To mitigate the risk of having each of these requesting teams waiting for requests to be fulfilled by the shared services team, we suggest thinking of the shared services as an open source project or as some call it – the contributor model.

Open sourcing our solution (at least internally) doesn’t mean opening up the email code base to all engineers and letting them have at it.  It does mean mechanisms should be established to help control the quality and design for the business. An open source project often has its own repo and typically only allows trusted engineers, called Committers, to commit. Committers have Contribution Standards defined by the project owning team. In our email example, the team should designate trusted and experienced engineers from other Agile teams that can code and commit to the email repo. Engineers on the email team can be focused on making sure new functionality aligns with architectural and design principles that have been established. Code reviews are conducting before its accepted. Allowing for outside contribution will help to mitigate the potential bottleneck such a team could create.

Now that the development of email has been spread out across contributors on different teams, who really owns it?

Remember, ownership by many is ownership by none.  In our example, the email team ultimately owns the services and code base. As other developers commit new code to the repo, the email team should conduct code, design, and architectural reviews and ultimately deployments and operations.  They should also confirm that the contributions align with the strategic direction of the email mission.  Whatever mechanisms are put in place, teams that adopt a contributor model should be a gas pedal and not a brake for TTM.

If your organization needs help with building an Agile organization that can innovate and achieve competitive TTM, we would love to partner with you. Contact us for a free consultation.

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The Top Five Most Common Agile PDLC Failures

April 27, 2018  |  Posted By: Dave Swenson
Top Five Agile Failures

Agile Software Development is a widely adopted methodology, and for good reason. When implemented properly, Agile can bring tremendous efficiencies, enabling your teams to move at their own pace, bringing your engineers closer to your customers, and delivering customer value
quicker with less risk. Yet, many companies fall short from realizing the full potential of Agile, treating it merely as a project management paradigm by picking and choosing a few Agile structural elements such as standups or retrospectives without actually changing the manner in which product delivery occurs. Managers in an Agile culture often forget that they are indeed still managers that need to measure and drive improvements across teams.

All too often, Agile is treated solely as an SDLC (Software Development Lifecycle), focused only upon the manner in which software is developed versus a PDLC (Product Development Lifecycle) that leads to incremental product discovery and spans the entire company, not just the Engineering department.


Here are the five most common Agile failures that we see with our clients:

     
  1. Technology Executives Abdicate Responsibility for their Team’s Effectiveness

Management in an Agile organization is certainly different than say a Waterfall-driven one. More autonomy is provided to Agile teams. Leadership within each team typically comes without a ‘Manager’ title. Often, this shift from a top-down, autocratic, “Do it this way” approach to a grass-roots, bottoms-up one sways way beyond desired autonomy towards anarchy, where teams have been given full freedom to pick their technologies, architecture, and even outcomes with no guardrails or constraints in place. See our Autonomy and Anarchy article for more on this. 


Executives often become focused solely on the removal of barriers the team calls out, rather than leading teams towards desired outcomes. They forget that their primary role in the company isn’t to keep their teams happy and content, but instead to ensure their teams are effectively achieving desired business-related outcomes.


The Agile technology executive is still responsible for their teams’ effectiveness in reaching specified outcomes (e.g.: achieve 2% lift in metric Y). She can allow a team to determine how they feel best to reach the outcome, within shared standards (e.g.: unit tests must be created, code reviews are required). She can encourage teams to experiment with new technologies on a limited basis, then apply those learnings or best practices across all teams. She must be able to compare the productivity and efficiencies from one team to another, ensuring all teams are reaching their full potential.

     
  1. No Metrics Are Used

The age-old saying “If you can’t measure it, you can’t improve it” still applies in an Agile organization. Yet, frequently Agile teams drop this basic tenet, perhaps believing that teams are self-aware and critical enough to know where improvements are required. Unfortunately, even the most transparent and aware individuals are biased, fall back on subjective characteristics (“The team is really working hard”), and need the grounding that quantifiable metrics provide. We are continually surprised at how many companies aren’t even measuring velocity, not necessarily to compare one team with another, but to compare a team’s sprint output vs. their prior ones. Other metrics still applicable in an Agile world include quality, estimation accuracy, predictability, percent of time spent coding, the ratio of enhancements vs. maintenance vs. tech debt paydown.

These metrics, their definitions and the means of measuring them should be standardized across the organization, with regular focus on results vs. desired goals. They should be designed to reveal structural hazards that are impeding team performance as well as best practices that should be adopted by all teams.

     
  1. Your Velocity is a Lie

Is your definition of velocity an honest one? Does it truly measure outcomes, or only effort? Are you consistent with your definition of ‘done’? Take a good look at how your teams are defining and measuring velocity. Is velocity only counted for true ‘ready to release’ tasks? If QA hasn’t been completed within a sprint, are the associated velocity points still counted or deferred?

Velocity should not be a measurement of how hard your teams are working, but instead an indicator of whether outcomes (again, e.g.: achieve 2% lift in metric Y) are likely to be realized - take credit for completion only when in the hands of customers.

     
  1. Failure to Leverage Agile for Product Discovery

From the Agile manifesto: “Our highest priority is to satisfy the customer through early and continuous delivery of valuable software”. Many companies work hard to get an Agile structure and its artifacts in place, but ignore the biggest benefit Agile can bring: iterative and continuous product discovery. Don’t break down a six-month waterfall project plan into two week sprints with standups and velocity measurements and declare Agile victory.


Work to create and deliver MVPs to your customers that allow you to test expected value and customer satisfaction without huge investment.

     
  1. Treating Agile as an SDLC vs. a PDLC

As explained in our article PDLC or SDLC, SDLC (Software Development Lifecycle) lives within PDLC (Product Development Lifecycle). Again, Agile should not be treated as a project management methodology, nor as a means of developing software. It should focus on your product, and hopefully the related customer success your product provides them. This means that Agile should permeate well beyond your developers, and include product and business personnel.


Business owners or their delegates (product owners) must be involved at every step of the PDLC process. PO’s need to be embedded within each Agile team, ideally colocated alongside team members. In order to provide product focus, POs should first bring to the team the targeted customer problem to be solved, rather than dictating only a solution, then work together with the team to implement the most effective solution to that problem.



AKF Partners helps companies transition to Agile as well as fine-tune their existing Agile processes. We can readily assess your PDLC, organization structure, metrics and personnel to provide a roadmap for you to reach the full value and benefits Agile can provide. Contact us to discuss how we can help.


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Evaluating Technology Risk Using Mathematics

April 23, 2018  |  Posted By: Geoffrey Weber

The Relative Risk Equation

Technologists are frequently asked: what are the chances that a given software release is going to work?  Do we understand the risk that each component or new feature brings to the entire release?  

In this case, measuring risk is assessing the probability that a component will perform poorly or even fail. The higher the probability of failure, the higher the risk.  Probabilities are just numbers, so ideally, we should be able to calculate the risk (probability of failure) of the entire release by aggregating the individual risk of each component.  In reality this calculation works quite well.

Putting a number to risk is a very useful tool and this article will provide a simple and easy way to calculate risk and produce a numeric result which can be used to compare risk across a spectrum of technology changes.

When we assess a system, one of the key characteristics we want to benchmark is the probability that a system will fail.  In particular, if we want to understand whether or not a system can support an availability goal of 99.95% we have to do some analysis to see if the probability that a failure occurs is lower than 0.05%. How do we calculate this?

First let’s introduce some vocabulary. 

DEFINITION: Pi is the probability that a given system will experience an incident, i. 

For the purposes of this article we are measuring relative and not absolute values.  A system where Pi=1 means the system is very unlikely to experience failure.  On other hand, Pi values approaching 10 indicate a system with a 100% probability of failure.  

DEFINITION: Iis the impact (or blast radius) a system failure will have.  

Ii=1 indicated no impact where Ii=10 indicates a complete failure of an entire system.

DEFINITION:  Pd is the probability that an incident will be detected.  

Pd=1 means an incident will be completely undetected and Pd=10 indicates that a failure will be completely detected 100% of the time.

Measuring across a scale from 1 to 10 is often too granular;  we can reduce scale to tee-shirt sizes and replace 1, 2, …, 10 with Small (3), Medium (5), Large (7). Any series of values will work so long as we are consistent in our approach.  

Relative Risk is now only a question of math: 

Ri = (Pi x  I) / Pd

With values of 1, 2, ..., 10, the minimum Relative Risk value is 0.1 (effectively 0 relative risk) and the maximum value is 100.  With tee-shirt sizes, the minimum Relative Risk value is 6/7 and the maximum value is 16.333.   Basic statistics can help us to standardize values from 1 to 10:

std(Ri)  = (Ri - Min(Ri)) / (Max(Ri)  - Min(Ri)) x 10 
where Max(Ri) = 16 1/3 and Min(Ri) = 1 2/7 (in the case of tee-shirt sizing)

For example:

Example 1: Adding a new data file to a relational database

  • Pi = 3 (low.). It’s unlikely that adding a data file will cause a system failure, unless we’re already out of space.
  • I = 5 (medium.). A failure to add a datafile indicates a larger storage issue may exist which would be very impactful for this database instance.  However as there is a backup (for this example), the risk is lowered.
  • Pd = 7 (high).  It is virtually certain that any failure would be noticed immediately.</li>
  • Therefore Ri = (3 X 5) / 7 = 2.1. Standardizing this to our 1 to 10 scale produces a value of 0.51.  That is a very low number, so adding datafiles is relatively low risk procedure.


Example 2: Database backups have been stored on tapes that have been demagnetized during transportation to offsite storage.

  • P= 5 (medium.). While restoring a backup is a relatively safe event, on a production system it is likely happening during a time of maximum stress.
  • I = 7 (high.). When we attempt to restore the backup tape, it will fail.
  • Pd= 3 (low.)  The demagnetization of the tapes was a silent and undetected failure.
  • Therefore Ri = (5 X 7) / 3 or 11.7.  We arrive at a value of 7 on the standard scale, which is quite high, so we should consider randomly testing tapes from off-site storage.


This formula has utility across a vast spectrum of technology:

  • Calculate a relative risk value for each feature in a software release, then take the total value of all features in order to compare risk of a release against other releases and consider more detailed testing for higher relative risk values.
  • During security risk analysis, calculate a relative risk value for each threat vector and sort the resulting values.  The result is a prioritized list of steps required to improve security based on the probabilistic likelihood that a threat vector will cause real damage.
  • During feature planning and prioritization exercises, this formula can be altered to calculate feature risk.  For example, Pi can mean confidence in estimate, Ii can be converted to impact of feature (e.g. higher revenue = higher impact) and Pd is perceived risk of the feature.  Putting all features through this calculation then sorting from high values to low values yields a list of features ranked by value and risk.

The purpose of this formula and similar methods is not to produce a mathematically absolute estimate of risk.  The real value here is to remove guessing and emotion from the process of evaluating risk and providing a framework to compare risk across a variety of changes.  

Click here to see how AKF Partners can help you manage risk and other technology issues.

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Avoiding the Policy Black Hole

April 18, 2018  |  Posted By: Pete Ferguson

During due diligence and in-depth engagements, we often hear feedback from client employees that policies either do not exist - or are not followed.

All too often we see policies that are poorly written, difficult for employees to understand or find, and lack clear alignment with the desired outcomes.  Policies are only one part of a successful program - without sound practices, policies alone will not ensure successful outcomes.

Do You Have a Policy …?

Early in my career I was volunteered to be responsible for PCI compliance shortly after eBay purchased PayPal.  I’d heard folklore of auditors at other companies coming in and turning things over with the resulting aftermath leading to people being publicly humiliated or losing their job.  I suddenly felt on the firing line and asking “why me?”

I booked a quick flight to Phoenix to be in town before the auditor arrived and I prepared by walking through our data center and reviewing our written policies.  When I met with the auditor, he looked to be in his early 20s and handed me a business card from a large accounting firm.  I asked him about his background; he was fresh out of college and we were one of his first due diligence assignments.  He pulled out his laptop and opened an Excel spreadsheet and began reading off the list:

  • Do you have cameras?  “Yes,” I replied and pointed to the ceiling in the lobby littered with little black domes.
  • Do you record the cameras?  “Yes,” and I took him into the control room and showed him that we had 90 days of recording.
  • Do you have a security policy?  “Yes,” and I showed him a Word Document starting with “1.1.1 Purpose of This Policy ....”

Several additional questions, and 10 minutes later, we were done.  He and I had both flown some distance so I gave him a tour of the data center and filled him full of facts about square footage and miles of cable and pipes until his eyes glossed over and his feet were tired from walking and off he went.

I was relieved, but let down!  I felt we had a really good program and wanted to see how we measured up under scrutiny.  Subsequent years brought more sophisticated reviews - and reviewers - but the one question I was always waiting to be asked - but never was:

“Is your policy easily accessible, how do employees know about it, and how do you measure their comprehension and compliance?”

My first compliance exercise didn’t seem all that scary after all, it was only a due diligence “check the box” exercise and didn’t dive deeper into how effective our program was and where it needed to be reinforced.

While having a policy for compliance requirements is important, on its own, policy does not guarantee positive outcomes.  Policy must be aligned with day-to-day operations and make sense to employees and customers.


The Traditional Boredom of Policy

Typically policy is written from the auditor’s point of view to ensure compliance to government and industry requirements for public health, anti-corruption, and customer data security standards. 


Image Credit: Imgur.com

Unfortunately, this leads to a very poor user experience wading through the 1.1.1 … 1.1.2 … . Certainly a far deviation from how a good novel or any online news story reads.

I’ve heard companies - both large and small - give great assurances that they have policies and they have shown me the 12pt Times New Roman documents that start with “1.1.1 Purpose of This Policy …” as evidence.

I had to argue the point at a former position that the first way to lose interest with any audience is to start with 1.1.1 … and with Times New Roman font in a Microsoft Word document that was not easy to find.  It was a difficult argument and I was instructed to stick with the approved, and traditional, industry-accepted method.

Fast forward a decade later and our HR Legal team was reviewing policy and invited me to a meeting with the internal communications team.  Before we started talking documents, the Director of Communications asked me if I’d seen the latest safety video for Virgin Atlantic Airlines.  I thought it a strange question, but after she told me how surprised and inspired by it she was, I took a look.

VA thankfully took a required dull and mundane US Federal Aviation Administration ritual and instead saw it as a differentiator of their brand from the pack of other airlines.  Whoever thought a safety demonstration could also be a 4-minute video on why an airline is different and fun?!?  Up until that point, no one!  Certainly not on any flight I had previously flown.

Thankfully, since then, Delta and others have followed their example and made something I and millions of airline crews and passengers had previously dreaded - safety policy and procedure - into a more fun, engaging, and entertaining experience.

While policy needs to comply with regulations and other requirements, for policies to move from the page to practice they need to be presented in a way employees clearly understand what is expected - so in writing policy, put the desired outcome first!  The regulatory document for auditors can be incorporated at the end of each policy or consider a separate document that calls out only the required sections of your employe handbook or where ever your company policies are presented and stored.

Clarifying the Purpose of Your Policy

In her article “Why Policies Don’t Work,” HR Lawyer Heather Bussing boils down the core issue: “There are two main reasons to have employment policies: to educate and to manage risk.  The trouble is that policies don’t do either.”

She further expounds on the problem in her experience:

“ … policies get handed out at a time when no one pays attention to them (first week of employment if not the first day), they are written by people who don’t know how the company really works (usually outside legal counsel), and they have very little to do with what happens.  So much for education.”

As for managing risk, Bussing points out that policies are often at odds with each other, or so broad that they can’t be effectively enforced.

“Unless it is required to be on a poster, or unless you can apply it in every instance without variance, you don’t want policies.  Your at-will policy covers it.  And if you don’t follow your policies to the letter, you will look like a liar in a courtroom.”

Don’t let your online policy repository feel like a suppository - focus on what you want to accomplish! 

Small and fast-growing companies typically have little need for formalized policies because people trust each other and can work things out.  But as they grow it has been my experience that often the trust and holding people accountable - which sets fast growing companies apart as a cool place to work - get replaced with bureaucratic rituals cemented in place as more and more executives migrate from larger, bureaucratic behemoths.  If the way policy is presented is the litmus test for the true company culture, a lot of companies are in trouble!

Policy must be closely aligned to the shared outcomes of the company and interwoven into company culture.  Otherwise they are a bureaucratic distraction and will only be adopted or sustained with a lot of uphill effort.  In short, if people do not understand how a policy helps them do their job more easily, they are going to fight it. 


Adapting Policy To Your Audience

In the early days of eBay, the culture was very much about collectables, and walking through the workspace many employees displayed their collections of trading cards, Legos, and comic books.  When it came time to publish our security policies, we hired Foxnoggin - a professional marketing strategy company - and took the time to get to understand our culture and then organized a comprehensive campaign to include contests, print and online material, and other collateral. 

They helped formulate an awareness campaign to educate employees and measure the effectiveness of policy through surveys and monitoring employee behavior.

To break away from the usual email method of communication, we got and held employee attention with a series of comic books which included superheroes and supervillains in a variety of scenarios highlighting our policies.

An unintended consequence from our collector employees was that they didn’t want to open their comic books and instead kept them sealed in plastic.  To combat this, we provided extra copies (not sealed in plastic) in break rooms and other common areas and future editions were provided without the bags.  The messages were reinforced with large movie-style posters displayed throughout the work area. 

This approach was wildly popular among employees located at the customer support and developer sites and surveys showed that security was becoming a top of mind topic for employees.  Unfortunately, this approach was not as popular with Europeans - who felt we were talking down to them - and by the executives coming from more stodgy and formal companies like Bain & Company or GE and particularly unpopular with execs from the financial industry after the purchase of PayPal.

Intertwining policy into the culture of your organization makes compliance natural and part of daily operations.

Make Sure Your Message Matches Your Audience

President and CEO of Lead From Within Lolly Daskal writes on Inc.com:

“... sometimes the dumbest rules can drive away the best employees … too many workplaces create rule-driven cultures that may keep management feeling like things are under control, but they squelch creativity and reinforce the ordinary.”

Be creative and look at the company culture and how to interweave policies.  Policies need to be part of the story you tell your employees to reinforce why they should want to work for you.

Nathan Christensen writes in his Fast Company article: How to Create An Employee Handbook People Will Actually Want to Read, “let’s face it, most handbooks aren’t exactly page-turners. They’re documents designed to play defense or, worse yet, a catalog of past workplace problems.”

Christensen recommends “presenting” policies in a readable and attractive manner.  It must be an opportunity to excite people in meeting a greater group purpose and cause.

Your policies need to match your company culture, be in language they use and and understand, and the ask for compliance needs to be easily enough for a new employee to be able to explain to anyone.

Writing Content Your Audience Will Actually Read and Understand

According to the Center for Plain Language - which has the goal to help organizations “write so clearly that their intended audience understands what they are saying the first time they read or hear it” - there are five steps to plain language:

  1. Identify and describe the target audience: “The audience definition works when you know who you are and are not designing for, what they want to do, and what they know and need to learn.”
  2. Structure the content to guide the reader through it: “The structure works when readers can quickly and confidently find the information they are looking for.”
  3. Write the content in plain language: “Use a conversational, rather than legal our bureaucratic tone … pick strong verbs in the active voice and use words the audience knows.”
  4. Use information design to help readers see and understand: Font choice, line spacing, and use of graphics help break up long sections of text and increase the readability score.
  5. Work with target user groups to test design and content: Ask readers to describe the content and have them show you where they would find relevant content.

As an illustration, here is a before and after comparison of the AARP Financial policy on giving and receiving gifts:

In reading the “before” example, my eyes immediately glazed over and my mind began to wander until the mention of “courtesies of a de minimus ... “ Did the guy who wrote that go home that night to his family and instruct his kids, “you will need to consume a courtesise of a de minimus amount of broccoli if you want videogame time after dinner”?  I sure hope not!

On the “after” example, notice the change in line spacing, switching of font and use of bullet points.  Overall the presentation is a lot more conversational and less formal.  It also has a call to action in the title starting with two verbs “give and accept …”

I’d add as the 6th step to remember K.I.S.S. - Keep It Simple Stupid!  You get a few seconds to grab your audience’s attention and only a few more minutes to keep it. 

As a content editor, I was feeling proud of myself when I distilled 146 pages of confusing policies, procedures and “how to” down to 14 pages over the course of several weeks.  But when I mentioned this to my wife, she said “you are going to make them read 14 pages?!?” 

So I looked at it a few days later with fresh eyes and realized I could condense it down again to two pages by making it more of a table of contents with a brief description of each bullet point and then include links after each section if employees wanted to learn more, and I was able to retain a font size of 14 and plenty of white space.

In reading the two pages, people would understand what was expected of them and could easily learn more - but only if they were interested.

Write policy in language a new employee will quickly understand and be thoughtful in how much you present to employees on their first day, week, and month.


Document Readability is How You Show Your People Love - And Soon To Be the Law In the EU

Speaking more in terms of content marketing, VisibleThread author “Fergle” quotes Neil Patel, columnist for Forbes, Inc, as stating “content that people love and content that people can read is almost the same thing.”  Yet, as Fergle points out, “a lot of content being created is not the stuff people love. Or read.”

“Content that people love and content that people can read is almost the same thing.”

Writing content with the aim of it being easy to read as something people love may seem a bit altruistic.  But for information regarding data privacy, it is also soon to be the law - at least in the EU and for any international policy which would reach an EU resident.  On May 28th of 2018 the General Data Protection Regulation (GDPR) goes into effect.  From the GDPR :

“The principle of transparency requires that any information and communication relating to the processing of those personal data be easily accessible and easy to understand, and that clear and plain language be used.”

There are a number of ways to measure readability ease and grade level of your content, and a good communications expert will be able to help you identify the proper tools.

Scores are a good benchmark, but don’t forget the most important resource for feedback - your potential audience! 

Buy them lunch, have them come and review your plan and provide their feedback.  Bring them back in later when you have content to review and provide an environment where they can be brutally honest - again a communications expert outside of your department will help provide a bit of a buffer and allow your audience to be open, honest, and direct.

But don’t just write policy to comply with due diligence or for policy’s sake - be sure it is part of the company culture, easy to search, and placed where and when your employees or customers will need it.  When there are shared outcomes between compliance and how employees operate, policy is integrated and effective. 

Timing is Important

Think of ways to break down your policy content not just by audience, but by timing and when the information will actually be relevant.

In retail, the term “point of sale” refers to the checkout process - when taxes, final cost and payment are all settled.  The placement of “last minute items” at the POS is very carefully, and competitively assigned only to items with a high ROI measured by the amount of inches each item takes up on the limited shelf space.  This careful placement has also been adopted to the online marketplace when you add an item to your shopping cart and a prompt arises to add additional items others have also purchased with your item.

This same methodology in thinking should be applied to where - and when - you introduce your policies to your audience.

We made the mistake for years of pushing our travel safety program and policies for everyone during new hire orientation when only about half of the population traveled and most of them wouldn’t be traveling for several weeks or months.  It made a lot more sense to move the travel policies to the travel booking page.

If you only give out corporate credit cards to Directors and above, there is no sense pushing policies on spend limits to the global population.  It makes a lot more sense to push the policy when someone is applying for the card and as a reminder each time their credit card expires and they are being issued a new one.

Your audience will appreciate only being told what they need to know when they need the information and will be more likely to not only retain the information, but to comply!


    For similar content on our Growth Blog, click here


Know How You Will Measure Successful Outcomes

Perhaps the most important question to ask when designing policy is “how we will know we are successful?” 

Having good policy written in a clear and concise manner and stored in an easy to find location is still a very passive approach.  Good policy should evolve as your company evolves and should be flexible and realistic to business, customer, and employee needs.  It must be modeled by company leadership and hold true to the daily actions of your company.

Tests at the end of annual compliance training are only a “check the box” measure of compliance.  Think back to how much you actually learned - or, better yet, retained - the last time you were subjected to hours of compliance training!

If metrics cannot support that your policies are known and followed, then you need to re-evaluate the purpose of your policies and if they are contributing to the benefit of your employees and customers or just ticking compliance boxes.

While compliance is important, compliance alone does not make for better business practices or a competitive edge.  Effective, measurable compliance protects your employees and provides value to your customers.

Getting Started

Subject-matter experts are often too close to the policies to be objective.  A little tough love is needed and it is best to bring in experts in marketing and communications who will not be biased to the content, but biased to the reader who is the intended audience. 

A good communications plan will cover the following:

  • Be clear on the desired behavior the policy is to encourage and enforce - and that behavior is streamlined with the overall company purpose
  • Identify the target audiences and each of their self-interests
  • Outline which channels each audience is receptive to (email/print/video, etc.)
  • Identify the inside jargon and language styles needed
  • Decide when and where each audience will want to find relevant information
  • Plan how often policies will be reviewed - and include as many stakeholders as possible in the review process
  • Decide how implementation of policies and compliance to the policies will be measured

Only AFTER the communications plan is agreed upon - with plenty of input from representatives of the target audiences - should the content review begin.  Otherwise the temptation from subject-matter experts will be to tell people everything they know.


Pulling it All Together

Poorly written policies that are difficult for employees to search or find do little to meet the mission of policy: to provide a consistent approach to how your company does business and satisfies regulatory compliance.  Policies on their own do not make for good operations or guarantee overall success.  Remember the true test of policies is not whether they exist, but if they are tightly aligned and incorporated into daily operations, how they contribute to the success of your employees and customers, and if their effectiveness can be measured in a tangible way.

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SaaS Migration Challenges

March 12, 2018  |  Posted By: Dave Swenson

AKF scale cube cloud computing SaaS conversion

More and more companies are waking up from the 20th century, realizing that their on-premise, packaged, waterfall paradigms no longer play in today’s SaaS, agile world. SaaS (Software as a Service) has taken over, and for good reason. Companies (and investors) long for the higher valuation and increased margins that SaaS’ economies of scale provide. Many of these same companies realize that in order to fully benefit from a SaaS model, they need to release far more frequently, enhancing their products through frequent iterative cycles rather than massive upgrades occurring only 4 times a year. So, they not only perform a ‘lift and shift’ into the cloud, they also move to an Agile PDLC. Customers, tired of incurring on-premise IT costs and risks, are also pushing their software vendors towards SaaS.

SaaS Migration is About More Than Just Technology – It is An Organization Reboot
But, what many of the companies migrating to SaaS don’t realize is that migrating to SaaS is not just a technology exercise.  Successful SaaS migrations require a ‘reboot’ of the entire company. Certainly, the technology organization will be most affected, but almost every department in a company will need to change. Sales teams need to pitch the product differently, selling a leased service vs. a purchased product, and must learn to address customers’ typical concerns around security. The role of professional services teams in SaaS drastically changes, and in most cases, shrinks. Customer support personnel should have far greater insight into reported problems. Product management in a SaaS world requires small, nimble enhancements vs. massive, ‘big-bang’ upgrades. Your marketing organization will potentially need to target a different type of customer for your initial SaaS releases - leveraging the Technology Adoption Lifecycle to identify early adopters of your product in order to inform a small initial release (Minimum Viable Product).

It is important to recognize the risks that will shift from your customers to you. In an on-premise (“on-prem”) product, your customer carries the burden of capacity planning, security, availability, disaster recovery. SaaS companies sell a service (we like to say an outcome), not just a bundle of software.  That service represents a shift of the risks once held by a customer to the company provisioning the service.  In most cases, understanding and properly addressing these risks are new undertakings for the company in question and not something for which they have the proper mindset or skills to be successful.

This company-wide reboot can certainly be a daunting challenge, but if approached carefully and honestly, addressing key questions up front, communicating, educating, and transparently addressing likely organizational and personnel changes along the way, it is an accomplishment that transforms, even reignites, a company.

This is the first in a series of articles that captures AKF’s observations and first-hand experiences in guiding companies through this process.


Don’t treat this as a simple rewrite of your existing product –
Answer these questions first…


Any company about to launch into a SaaS migration should first take a long, hard look at their current product, determining what out of the legacy product is not worth carrying forward. Is all of that existing functionality really being used, and still relevant? Prior to any move towards SaaS, the following questions and issues need to be addressed:

Customization or Configuration?
SaaS efficiencies come from many angles, but certainly one of those is having a single codebase for all customers. If your product today is highly customized, where code has been written and is in use for specific customers, you’ve got a tough question to address. Most product variances can likely be handled through configuration, a data-driven mechanism that enables/disables or otherwise shapes functionality for each customer. No customer-specific code from the legacy product should be carried forward unless it is expected to be used by multiple clients. Note that this shift has implications on how a sales force promotes the product (they can no longer promise to build whatever a potential customer wants, but must sell the current, existing functionality) as well as professional services (no customizations means less work for them).

Single/Multi/All-Tenancy?
Many customers, even those who accept the improved security posture a cloud-hosted product provides over their own on-premise infrastructure, absolutely freak when they hear that their data will coexist with other customers’ data in a single multi-tenant instance, no matter what access management mechanisms exist. Multi-tenancy is another key to achieving economies of scale that bring greater SaaS efficiencies. Don’t let go of it easily, but if you must, price extra for it.

Who Owns the Data?
Many products focus only on the transactional set of functionality, leaving the analytics side to their customers. In an on-premise scenario, where the data resides in the customers’ facilities, ownership of the data is clear. Customers are free to slice & dice the data as they please. When that data is hosted, particularly in a multi-tenant scenario where multiple customers’ data lives in the same database, direct customer access presents significant challenges. Beyond the obvious related security issues is the need to keep your customers abreast of the more frequent updates that occur with SaaS product iterations. The decision is whether you replicate customer data into read-only instances, provide bulk export into their own hosted databases, or build analytics into your product?

All of these have costs - ensure you’re passing those on to your customers who need this functionality.

May I Upgrade Now?
Today, do your customers require permission for you to upgrade their installation? You’ll need to change that behavior to realize another SaaS efficiency - supporting of as few versions as possible. Ideally, you’ll typically only support a single version (other than during deployment). If your customers need to ‘bless’ a release before migrating on to it, you’re doing it wrong. Your releases should be small, incremental enhancements, potentially even reaching continuous deployment. Therefore, the changes should be far easier to accept and learn than the prior big-bang, huge upgrades of the past. If absolutely necessary, create a sandbox for customers to access new releases, but be prepared to deal with the potentially unwanted, non-representative feedback from the select few who try it out in that sandbox.

Wait? Who Are We Targeting?
All of the questions above lead to this fundamental issue: Are tomorrow’s SaaS customers the same as today’s? The answer? Not necessarily. First, in order to migrate existing customers on to your bright, shiny new SaaS platform, you’ll need to have functional parity with the legacy product. Reaching that parity will take significant effort and lead to a big-bang approach. Instead, pick a subset or an MVP of existing functionality, and find new customers who will be satisfied with that. Then, after proving out the SaaS architecture and related processes, gradually migrate more and more functionality, and once functional parity is close, move existing customers on to your SaaS platform.

To find those new customers interested in placing their bets on your initial SaaS MVP, you’ll need to shift your current focus on the right side of the Technology Adoption Lifecycle (TALC) to the left - from your current ‘Late Majority’ or ‘Laggards’ to ‘Early Adopters’ or ‘Early Majority’. Ideally, those customers on the left side of the TALC will be slightly more forgiving of the ‘learnings’ you’ll face along the way, as well as prove to be far more valuable partners with you as you further enhance your MVP.

The key is to think out of the existing box your customers are in, to reset your TALC targeting and to consider a new breed of customer, one that doesn’t need all that you’ve built, is willing to be an early adopter, and will be a cooperative partner throughout the process.


Our next article on SaaS migration will touch on organizational approaches, particularly during the build-out of the SaaS product, and the paradigm shifts your product and engineering teams need to embrace in order to be successful.

AKF has led many companies on their journey to SaaS, often getting called in as that journey has been derailed. We’ve seen the many potholes and pitfalls and have learned how to avoid them. Let us help you move your product into the 21st century.  See our SaaS Migration service


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