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Factors Driving SaaS and XaaS Adoption

July 12, 2018  |  Posted By: Marty Abbott

XaaS (e.g. SaaS, PaaS) mass-market adoption is largely a demand-side “pull” of a product through the Technology Adoption Lifecycle (TALC).  One of the best books describing this phenomenon is the book that made the TALC truly accessible to business executives in technology companies, Crossing the Chasm.

Technology Adoption Life Cycle Adopter Characteristics

An interesting side note here is that Crossing the Chasm was originally published in 1991.  While many people associate the TALC with Geoffrey Moore, it’s actual origin is Everett Rogers’ research on the diffusion of innovations.  Rogers’ initial research focused on the adoption of hybrid corn seed by rural farmers.  Rogers and team expanded upon and generalized the research between 1957 and 1962 when he released his book Diffusion of Innovations.  While the 1962 book was a critical success, I find it interesting that it took nearly 30 years to bring the work to most technology business executives.

Several forces combine to incent companies within each phase of the TALC to consider, and ultimately adopt, XaaS solutions.  Progressing from left to right through the TALC, companies within each phase are decreasingly less aware of these forces and increasingly more resistant to them until the forces are overwhelming for that segment or phase.  Innovators, therefore, are the most aware of emerging forces, seek to use them for competitive advantage and as a result are least resistant to them.  Laggards are least aware (think heads in the sand) and most resistant to change, desiring status quo over differentiation. 

While the list below is incomplete, it has a high degree of occurrence across industries and products.  Our experience is that even when they are experienced in isolation (without other demand side XaaS forces), they are sufficient to pull new XaaS products across the TALC.


Demand Side Forces

Factors Driving SaaS Adoption

Talent Forces:  Opportunity, Supply and Demand

The first two forces represent the talent available to the traditional internally focused corporate IT organization.  The rise of XaaS offerings and the equity compensation opportunities inherent to them has been a vacuum sucking what little great talent exists within corporate IT.  This first force really serves to add insult to injury to the second force: the initial low supply of talented engineers available in the US. 

Think about this:  Per-capita (normalized for population growth) US graduates for engineers within the US has remained relatively constant since 1945.  While there has been absolute growth, until very recently that growth has slightly underperformed relative to the growth in population.  Contrast this with the fact that college graduation rates in 2012 were higher than high school graduation rates in 1940.  Add in that most engineering fields were at or near economic full employment during the great recession and we have a clear indication that we simply do not produce enough engineers for our needs.  The same is true on a global level.

This constrained supply has led to alternative means of educating programmers, systems administrators, database administrators and data analysts.  “Boot Camps”, or short courses meant to help teach people basic skills to contribute to the product and IT workforces, have sprung up around the nation to help fulfill this need.  Once trained, the people fulfill many lower level needs in the product and IT space, but they are not typically equivalent to engineers with undergraduate degrees.

Constrained supply, growing demand and a clear differentiation in employment for engineers working in product organizations compared to IT organizations means that IT groups simply aren’t going to get great talent.  Without great talent, there can be no great development or operations teams to create or run solutions.  As such, the talent forces alone mandate that many IT teams look to outsource as much as they can:  everything from infrastructure to the platforms that help make employees more efficient.

Core vs. Context

Why would a company spend time or capital on running third party solutions or developing bespoke solutions unless those activities result in competitive differentiation?  Doing so is a waste of precious time and focus.  Companies simply can’t waste time running email servers, or building CRM solutions and soon will find themselves not spending time on anything that doesn’t directly lend itself to competitive advantage.

Factors Driving SaaS Adoption

Margins

Put simply, anytime a company can’t maximize profit margins through keeping in-house systems highly utilized, they should (and will) seek to outsource the workload to an IaaS provider.  Why purchase a server to do work 8 hours a day and sit idle 16?  Why purchase a server capable of handling peak period of 10 minutes of traffic, when a server one fifth its size is all that’s needed for the remainder of the day? 

Part of staying competitive is focusing on profit maximization to invest those profits in other, higher return opportunities.  Companies that don’t at least leverage Infrastructure as a Service to optimize their costs of operations and costs of goods sold (if doing so results in lowered COGS) are arguably violating their fiduciary responsibility.

Risk

Risk is the probability that an event occurs, multiplied by the impact of that event should it occur.  Companies that specialize in providing a service, whether it be infrastructure as a service or software as a service typically have better skills and more experience in providing that service than other companies.  This means that they can both reduce the probability of occurrence and likely the impact of the occurrence should it happen.  Anytime such a risk shift is possible, where company A can shift its risk of operating component B to a company C specializing in managing that risk at an affordable price, it should be taken.  The XaaS movement provides many such opportunities.

Time to Market

One of the most significant reasons why companies choose either SaaS or IaaS solutions is the time to market benefit that their usage provides.  In the SaaS world, it’s faster and easier to launch a solution that provides compelling business efficiencies than purchasing, implementing and running that system in-house.  In the IaaS world, infrastructure on demand is possible and companies need not wait for onerous lead times associated with ordering and provisioning equipment.

Factors Driving SaaS Adoption

Focus on Returns

Most projects, including packaged software purchased and implemented on site are delivered late and fail to produce the returns on which the purchase was predicated.  Further, these projects are “hard to kill”, with millions invested and long depreciation cycles; companies are financially motivated to “ride” their investments to the bitter end in the hopes of minimizing the loss.  In the extreme, XaaS solutions offer a simple way to flee a sinking ship:  leave.  Because the solution is leased, you can (obviously with some work) switch to a competing provider.  Capital is freed up in the company for higher return investments associated with revenue rather than costs.

Factors Driving SaaS Adoption

Factor Outcomes

The outcomes of these factors is clear.  In virtually every industry, and for nearly every product, companies will move from on-premise or built-in-house solutions to XaaS solutions.  CEOs, COOs, CTOs and CIOs will all seek to “Get this stuff out of my shop!” 

Companies that believe it will never happen in their industry are simply kidding themselves and completely ignoring the outcomes predicted within the technology adoption life-cycle.  Every company needs to focus on fewer, higher value things.  Every company should outsource risky operational activities if there is a better manager of that risk than them.  Every company is obligated to seek better margins and greater profitability – even those companies in the not for profit sector need to maximize the benefit of every donated dollar.  Every company seeks opportunities to bring their value to market faster.  And finally, few companies can find the great talent in today’s market necessary to be successful in their corporate IT and product operations endeavors. 

If you produce on-premise, licensed software products and have not yet considered the movement to a SaaS solution, you need to do so now.  Failing to do so could mean the demise of your company.

We are experts in helping companies migrate products to the XaaS model.  Contact us - we would love to help you.

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SaaS Principles Part 2

June 29, 2018  |  Posted By: Marty Abbott

Following our first article on the conflict between licensed products and SaaS solutions, we now present a necessary (but not always sufficient) list of SaaS operating principles.  These principles are important whether one is building a new XaaS (PaaS, SaaS, IaaS) solution, or migrating to an XaaS solution from an on-premise, licensed product.

These principles are developed from the perspective of the product and engineering organization, but with business value (e.g. margins) in mind.  They do not address the financial or other business operations needs within a SaaS product company.

1. Build to Market Need – Not Customer Want
Reason:  Smaller product (less bloat).  Lower Cost of Goods (COGS).  Lower R&D cost.
Customer “wants” now help inform and validate professional product management analysis as to what true market “need” is for a product.  Products are based on the minimum viable product concept and iterated through a scientific method of developing a hypothesis, testing that hypothesis, correcting where necessary and expanding it when appropriate.  Sales teams need to learn to sell “the cars that are on the lot”, not sell something that is not available.  Smaller, less bloated, and more configurable products are cheaper to operate, and less costly to maintain.

2. Build “-ilities” First
Reason:  Availability, Customer Retention, and high Revenue Retention.
Availability, scalability, reliability, and nearly always on “utility” are now a must have, as the risk of failure moves from the customer in the on-premise world to the service provider.  No longer can product managers ignore what was once known as NFRs or “Non-Functional Requirements”.  The solution must always meet, as a bare minimum, the availability and response times necessary to be successful while scaling in a multi-tenant way under hopefully (significant) demand.

3. Design to be Monitored
Reason:  Availability, Customer Retention, and high Revenue Retention.
Sometimes considered part of the “ilities” to achieve specifically high availability, we call this one out specifically as engineers must completely change behavior.  Like the notion of test driven development, this principle requires that engineers think about how to log and create data to validate that the solution works as expected before starting development.  Gone are the days of closing a defect as “working as designed” – we now promote solutions to production that can easily validate usage and value creation and we concern ourselves only with “Does it work as expected for customer benefit?”

4. Design for Easy and Efficient Operations – Automate Always
Reason:  Lower COGS.  Availability.
Everything we do to develop product and deliver a customer experience needs to be enabled through automation:  environment creation, product releases, system analysis, database upgrades, etc.  Whether this happens within a traditional operations team, a DevOps group, or product engineering, automation is part of our “whole product” and “ships” with our service solution upgrades.

5. Design for Low Cost of Operations
Reason:  Lower COGS.
Automation helps us lower the cost of operations, but we must also be cognizant of infrastructure related costs.  How do we limit network utilization overall, such that we can lower our costs associated with transit fees?  How do we use less memory footprint and fewer compute cycles to perform the same activity, such that we can reduce server infrastructure related costs?  What do we really need to keep in terms of data to reduce storage related costs?  Few if any of these things are our concerns on-premise, but they all affect gross margin when we run a SaaS business.

6. Engage Developers in Incident Resolution and Post Mortems
Reason:  Faster Time to Resolution.  Availability.  Better Learning Processes.
On premise companies value developer time because new feature creation trumps everything else.  SaaS companies know that restoring services is more important than anything else.  Further, developers must understand and “feel” customer pain.  There is no better motivation for ensuring that problems do not recur, and that we create a learning organization, than ensuring engineers understand the pain and cost of failure.

7. Configuration over Customization
Reason:  Smaller Product.  Lower COGS.  Lower R&D Cost.  Higher Quality.
One “core”, lots of configuration, no customization is the mantra of every great SaaS company.  This principle enables others, and aids in creating a smaller code base with lower development costs and lower costs of operations.  Lower cyclomatic complexity means higher quality, lower cost of future augmentation, and lower overall maintenance costs.

8. Create and Maintain a Homogeneous Environment
Reason:  Lower COGS.
Just as the software that enables our product should not be unique per customer, similarly the infrastructure and configuration of our infrastructure should not be unique per customer.  Everyone orders off the menu, and the chef does not create something special for you.  The menu offers opportunities for configurations – sometimes at costs (e.g. bacon on your burger) but you cannot substitute if the menu does not indicate it (e.g. no chicken breast).

9. Publish One Single Release for All Customers
Reason:  Decreased COGS.  Decreased R&D Cost (low cost of maintenance).
The licensed software world is lousy with a large engineering burden associated with supporting multiple releases.  The SaaS world attempts to increase operating margins by significantly decreasing, ideally to one, the number of versions supported for any product.

10. Evolve Your Services, Don’t Revolutionize Them
Reason:  Easier Upgrades.  Availability.  Lower COGS.
No customer wants downtime associated with an upgrade.  The notion is just ridiculous.  How often does your utility company take your service offline (power for instance) because they need to perform an “upgrade”?  Infrequently (nearly never) at best – and if/when they do it is a giant pain for all customers.  Our upgrades need to be simple and small, capable of being reversed, and “boil the frog” as the rather morbid saying goes.  No more large upgrades with significant changes to data models requiring hours of downtime and months of preparation on the part of a customer.

11. Provide Frequent Updates
Reason:  Smaller product (less bloat).  Lower COGS.  Lower R&D cost.  Faster Time to Market (TTM).
Pursuant to the evolutionary principle above, updates need to happen frequently.  These two principles are really virtuous (or if not performed properly, vicious) when related to each other.  Doing small upgrades, as solutions are ready to ship, means that customers (and our company) benefit from the value the upgrades engender sooner.  Further, small upgrades mean incremental (evolutionary) changes.  Faster value, smaller impact.  It cures all ills and is both a dessert topping and floor wax.

12. Hire and Promote Experienced SaaS Talent
Reason:  Ability to Achieve Goals and SaaS Principles.
Running SaaS businesses, and developing SaaS products require different skills, knowledge and behaviors than licensed, on premise products.  While many of these can be learned or trained, attempting to be successful in the XaaS world without ensuring that you have the right knowledge, skills, and abilities on the team early on is equivalent to assuming that all athletes can play all sports.  Assembling a football team out of basketball players is unlikely to land you in the Super Bowl.

13. Restrict Access
Reason:  Lower Risk.  Higher Availability.
Licensed product engineers rarely have access to customer production environments.  But in our new world, its easy to grant it and in many ways it can be beneficial.  Unfortunately, unfettered access increases the risk of security breaches.  As such, we both need to restrict access to production environments and ensure that the engineering team has access to appropriate trouble shooting data outside of the production environment to ensure rapid problem and incident resolution.

14. Implement Multi-Tenancy
Reason:  Lower COGS.
Solutions should be multi-tenant to enable better resource utilization, but never all-tenant to ensure that we have proper fault isolation and appropriate availability.


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SaaS Principles Part 1 - The Conflict between Licensed Software and SaaS

June 22, 2018  |  Posted By: Marty Abbott

Photo Credit: icomputerdenver.com
Photo Credit: www.icomputerdenver.com


Attempting to migrate on-premise, licensed products to a recurring revenue SaaS (XaaS) solution is perhaps one of the most difficult things a company can do.  As Dave Swenson writes in SaaS Migration Challenges, changes are often necessary to the fabric of the company, including the company culture and mindset.

In many cases, the principles that make a company successful in the on-premise, packaged software model are insurmountable barriers to success in XaaS.  As an example of the difficulty of this transition, consider one group of opposing principles endemic to SaaS transition:  building to customer want (licensed model) versus building to market need (SaaS model).  For years, on-premise providers were successful by filling their product backlog with customer requests (or “wants”).  When requests were specific to a single customer and didn’t appear to be extensible to a broader base, a revenue stream associated with professional services was created.  Professional services, or a system integrator, would make modifications to source code creating a unique “version” for that customer.  This approach led to bloated products, oftentimes with a single customer using less than 30% of a product’s capabilities.  Moreover, release “skew” developed, increasing the cost of maintenance of multiple releases in “the wild”.

Contrast this with a product approach that attempts to “discover” the intersection of true market need.  Product backlogs are built primarily on thorough market analysis coupled with experimentation.  Customer asks (or “wants”) help inform prioritization, but are not the primary driver of product backlog.  Sales organizations focus on selling the existing product rather than driving it, and the role of professional product managers emerge.  This notion of “want” vs. “need” is critical to the success of a company’s transformation.

The difficulty of such a journey from “want” in the licensed product world to “need” in the XaaS world should be clear to everyone.  If the difficulty is high in a transition, imagine the stressful forces a company must endure to live in both worlds for an extended period of time.  Sales organizations that build upon selling a customer “whatever they desire” often revolt at being relegated to selling only what exists.  Product management organizations that previously acted like “business analysts” taking requirements, now need to perform real market analysis, understand discovery and experimentation and get “closer to the market”.  How does one build a company that can be successful in both worlds at once?  Difficult indeed given the chasm between one approach and the other.

The figures below indicate a handful of the most common opposing forces as examples of how companies need to “reinvent themselves” and think differently to be successful as a XaaS provider.

Conflict between successful licensed software and SaaS principles slide 1

Purchase versus Lease

At the root of many of the differences between Licensed/On-Premise products (or licensed products that are hosted in ASP-like models) and true XaaS products is the notion of what the customer expects with the sales transaction.  In the licensed model, customers want outcomes but understand they are purchasing software.  The customer understands that much of the risk of running the software including the “ilities” like availability and scalability are borne by the customer.

In the SaaS world, the customer mindset is that of leasing outcomes.  Comparatively low switching costs (compared to on-premise) allows the customer to more easily move should they not achieve their desired outcomes.  As such, service providers must move closer to the customer and better understand, in real time, customer expectations and the product’s performance to those expectations.

To highlight this difference, consider the difference between renting a home and owning a home.  In most markets, the total cost of rent against the combination of amortized home values over an equivalent period and the residual (resale value) of the home indicates that renting is more expensive.  But a majority of the risk of renting exists with the leasor including home maintenance, risk associated with loss to catastrophe, etc.  The same is true with SaaS compared to owning a product:  SaaS requires the service provider to take on significantly greater risk compared to selling a product to a customer.

Want versus Need

Henry Ford perhaps said it best when he said, “If I’d asked customers what they want, they would have told me a faster horse.”  Steve Jobs agreed with Ford, indicating that people don’t know what they want until you show it to them.  Here Steve is referring to true “need” vs. a stated customer “want”.  Licensed products often start with customer wants.  Sales teams garner desires, and either force them into product backlogs or sell modifications through professional services.  Because the customer purchases the software, the company isn’t as incented as the SaaS model to ensure that the customer gets value from that which they purchased.  The product development lifecycle, regardless of how it is represented to the customer, is almost always in fact waterfall.

XaaS companies attempt to “find” (aka discover) market need.  Product managers analyze markets, establish goals, create hypotheses to achieve these goals, and co-create solutions to test these hypotheses with their engineering teams.  What a customer may indicate as a “want” may help inform prioritization of the backlog especially if there is an intersection in customer desired outcomes.

Operations Afterthought versus Designed for Efficient Operations

In the on-premise world, the customer is responsible for the cost of operations and the effective and efficient operations of any solution.  Considerations such as monitoring for early fault and incident detection are at best after thoughts in the world of on-premise software development, giving rise to an industry specializing in after market monitoring.  The reasoning behind this approach is clear – time spent producing efficient solutions that can be easily maintained takes away from new feature development and new revenue associated with those features.

In the SaaS world, we are responsible for our own cost of operations and therefore building products that operate efficiently with low cost of goods sold is important to achieving high gross margins and profit margins.  Furthermore, as we are responsible for all the “ilities” (described below), we must design our solutions to be monitored in real time to detect errors, faults, problems and incidents.

Revolutionary versus Evolutionary

Put simply, on-premise models rely on “fork-lift” major product upgrades that often take significant effort, downtime and customer expense to implement.  The latter is often seen as a bonus to the provider of software, as upgrades can become an additional revenue stream for professional services both in assisting with the upgrade and re-implementing customizations lost during the upgrade.

XaaS products simply can’t afford the downtime, or cost associated with revolutionary implementations.  As such data models and functionality evolve quickly but iteratively with the capability to completely roll back or “undo” both schema modifications and functionality additions. 

Conflict between successful licensed software and SaaS principles slide 2

Many Releases versus Single Release

Because on-premise companies can rarely force patch or release adoption across their installed base (they typically have no access to these environments), the number of releases they support may be in the 100s or even 1000s.  This release skew increases operating expenses as a large portion of engineering may be spent supporting problems across a very large number of releases.

SaaS companies recognize that release skew increases the cost of development, and as such, force most customers into a single (or no more than 3) releases.  Companies that fail in this principle face on-premise-like operating margins as engineering budgets increase to support releases.

Customization Equals Revenue versus Customization Equals Cost of Operations

On premise companies see customization as a valuable revenue stream, often at the expense of increased engineering budgets to support the maintenance of these customizations and the distractions they cause.

SaaS companies abhor customization and favor configuration, leading to higher quality products and better overall customer experiences.

Features First versus “-ilities” First

While all of the XaaS principles are important, one of the most difficult to grasp for our on-premise clients is the notion that the “-ilities” (sometimes called NFRs or Non Functional Requirements in waterfall development) like availability, scalability, reliability, etc are now the most important feature within their products.  It pains me to even call them a feature, as they are the “table stakes” (the ante, the price we pay) for the game in which we participate.

License/on-premise companies can punt on the “-ilities” because the customer is accountable for running the solution and bears a good portion of the risk.  Availability impacts like hardware failures are ultimately the responsibility of the customer.  The decision to pay for high availability represented through infrastructure is also the responsibility of the customer. 

These “-ilities” steal time from engineering teams – and appropriately so – to ensure the quality of the service provided.  Feature production is still important – it’s just second in line behind ensuring that the solution is available for value creation.

Developers Protected versus Developers Front-Lines

Because feature production is highly correlated with revenue in the licensed software model, companies often protect developer time with multiple layers of support.  When customers have outages, companies attempt to resolve them with lower cost support personnel before stealing development time from critical projects.  Licensed product companies can get away with this because when there is a failure at a customer site a comparatively small portion of revenue and customer base is at risk.

In the XaaS model, multiple customers are likely impacted with any outage due to increased tenancy.  And because we believe that availability is one of the most important features, we must respond with the resources necessary to resolve an incident as quickly as possible.

This is yet another sticking point with companies making the SaaS transition:  sometimes significant portions of engineering organizations do not want to be on call.  Those people simply have no role in a utility company-like model where “dial tone” is essential.

Up Next…

Part 2 describes a set SaaS principles derived from the conflict inherent to a migration from licensed products to the XaaS model.

Conclusion

The move from on-premise, licensed software revenue models to XaaS models is difficult.  Many of the principles that make an on-premise company successful are diametrically opposed to success in SaaS.  The longer a company must operate in both models, the more likely the culture, mindset and fabric of the company will be stretched.  Many successful companies decide to operate the two businesses separately, to ensure that one culture is not influenced negatively by the other.

AKF Partners has aided a number of companies in their journey from on-premise to SaaS.  Read more about our SaaS migration services.

 

 

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Multi-Tenant Defined

June 11, 2018  |  Posted By: Marty Abbott

Of the many SaaS operating principles, perhaps one of the most misunderstood is the principle of tenancy.

Most people have a definition in their mind for the term “multi-tenant”.  Unfortunately, because the term has so many valid interpretations its usage can sometimes be confusing.  Does multi-tenant refer to the physical or logical implementation of our product?  What does multi-tenant mean when it comes to an implementation in a database?

This article first covers the goals of increasing tenancy within solutions, then delves into the various meanings of tenancy.

Multi-Tenant (Multitenant) Solutions and Cost

One of the primary reasons why companies that present products as a service strive for higher levels of tenancy is the cost reduction it affords the company in presenting a service.  With multiple customers sharing applications and infrastructure, system utilization goes up:  We get more value production out of each server that we use, or alternatively we get greater asset utilization.  Because most companies view the cost of serving customers as a “Cost of Goods Sold’, multitenant solutions have better gross margins than single-tenant solutions.  The X Axis of the figure below shows the effect of increasing tenancy on the cost of goods sold on a per customer basis:

On Prem vs ASP vs SaaS models and cost implications

Interestingly, multitenant solutions often “force” another SaaS principle to be true:  No more than 1 to 3 versions of software for the entire customer base.  This is especially true if the database is shared at a logical (row-level) basis (more on that later).  Lowering the number of versions of the product, decreases the operating expense necessary to maintain multiple versions and therefore also increases operating margins.

Single Tenant, Multi-Tenant and All-Tenant

An important point to keep in mind is that “tenancy” occurs along a spectrum moving from single-tenant to all-tenant.  Multitenant is any solution where the number of tenants from a physical or logical perspective is greater than one, including all-tenant implementations.  As tenancy increases, so does Cost of Goods Sold (COGS from the above figure) decrease and Gross Margins increase. 

The problem with All-Tenant solutions, while attractive from a cost perspective, is that they create a single failure domain [insert https://akfpartners.com/growth-blog/fault-isolation], thereby decreasing overall availability.  When something goes poorly with our product, everything is off line.  For that reason, we differentiate between solutions that enable multi-tenancy for cost reasons and all-tenant solutions. 

Multi-tenancy compared to single-tenant and all tenant

The Many Meanings and Implementations of Tenancy

Multitenant solutions can be implemented in many ways and at many tiers.

Physical and Logical

Physical multi-tenancy is having multiple customers share a number of servers.  This helps increase the overall utilization of these servers and therefore reduce costs of goods sold.  Customers need not share the application for a solution to be physically multitenant.  One could, for instance, run a webserver, application server or database per customer.  Many customers with concerns over data separation and privacy are fine with physical multitenancy as long as their data is logically separated.

Logical multi-tenancy is having data share the same application.  The same webserver instances, application server instances and database is used for any customer.  The situation becomes a bit murkier however when it comes to databases.

Different relational databases use different terms for similar implementations.  A SQLServer database, for instance, looks very much like an Oracle Schema.  Within databases, a solution can be logically multitenant by either implementing tenancy in a table (we call that row level multitenancy) or within a schema/database (we call that schema multitenancy).  In either case, a single instance of the relational database management system or software (RDBMS) is used, while customer transactions are separated by a customer id inside a table, or by database/schema id if separated as such.

While physical multitenancy provides cost benefits, logical multitenancy often provides significantly greater cost benefits.  Because applications are shared, we need less system overhead to run an application for each customer and thusly can get even greater throughput and efficiencies out of our physical or virtualized servers.

Depth of Multi-Tenancy

The diagram below helps to illustrate that every layer in our service architecture has an impact to multi-tenancy.  We can be physically or logically multi-tenant at the network layer, the web server layer, the application layer and the persistence or database layer.

The deeper into the stack our tenancy goes, the greater the beneficial impact (cost savings) to costs of goods sold and the higher our gross margins.

Review of tenancy options in the traditional deployment stack

The AKF Multi-Tenant Cube

To further the understanding of tenancy, we introduce the AKF Multi-Tenant Cube. 
Multi-tenancy and cost implications mapped by degree, mode and type of multi-tenancy

The X axis describes the “mode’ of tenancy, moving from shared nothing, to physical, to logical.  As we progress from sharing nothing to sharing everything, utilization goes up and cost of goods sold goes down.

The Y axis describes the depth of tenancy from shared nothing, through network, web, app and finally persistence or database tier.  Again, as the depth of tenancy increase, so do Gross Margins.

The Z axis describes the degree of tenancy, or the number of tenants.  Higher levels of tenancy decrease costs of goods sold, but architecturally we never want a failure domain that encompasses all tenants. 

When running a XaaS (SaaS, etc) business, we are best off implementing logical multitenancy through every layer of our architecture.  While we want tenancy to be high per instance, we also do not want all tenants to be in a single implementation.

AKF Partners helps companies of all sizes achieve their availability, time to market, scalability, cost and business goals.

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The Many Unfortunate Meanings of Cloud

June 5, 2018  |  Posted By: Marty Abbott

Enough is enough already – stop using the term “Cloud”.  Somewhere during the last 20 years, the term “Cloud” started to mean to product offerings what Sriracha and Tabasco mean to food:  everything’s better if we can just find a way to incorporate it.  Just as Sriracha makes barely edible items palatable and further enhances the flavor of delicacies, so evidently does “Cloud” confuse the unsophisticated buyer or investor and enhance the value for more sophisticated buyers and investors. That’s a nice analogy, but it’s also bullshit.

The term cloud just means too many things – some of which are shown below:


various meanings of the word cloud and the confusion it causes


The real world of cloud offerings can be roughly separated into two groups:

  1. Pretenders This group of companies know, at some level, that they haven’t turned the corner and started truly offering “services”.  They support heavy customization, are addicted to maintenance revenue streams, and offer low levels of tenancy.  These companies simply can’t escape the sins of their past.  Instead, they slap the term “cloud” on their product in the hopes of being seen as being relevant.  At worst, it’s an outright lie.  At best, it’s slightly misleading relative to the intended meaning of the term.  Unless, of course, anything that’s accessible through a browser is “Cloud”.  These companies should stop using the term because deep down, when they are alone with a glass of bourbon, they know they aren’t a “cloud company”.
  2. Contenders This group of companies either blazed a path for the move to services offerings (think rentable instead of purchasable) products or quickly recognized the services revolution; they were “born cloud” or are truly embracing the cloud model.  They prefer configuration over customization, and stick to the notion of a small number of releases (countable on one hand) in production across their entire customer base.  They embrace physical and logical multi-tenancy both to increase margins and decrease customer costs.  These are the companies that pay the tax for the term “cloud” – a tax that funds the welfare checks for the “pretenders”.

The graph below plots Cloud Pretenders, Contenders and Not Cloud products along the axes of gross margin and operating margin:

Various models of cloud and on-premise plotted against cost of goods sold and operating expense

Consider one type of “Pretender” – the case of a company hosting a single tenant, client customized software release for each of their many customers.  This is an ASP (Application Service Provider) model.  But there is a reason the provider of the service won’t call themselves an ASP:  The margins of an ASP stinks relative to that of a true “SaaS” company.  The term ASP is old and antiquated.  The fix?  Just pour a bit of “cloud sauce” on it and everything will be fine.
Contrast the above case with that of a “Contender”:  physical and logical multi-tenancy at every layer of the architecture and \ a small number of production releases (one to three) across the entire customer base.  Both operating and gross margins increase as maintenance costs and hosting costs decrease when allocated across the entire customer base. 
Confused?  So are we.  Here are a few key takeaways:

  1. “Cloud” should mean more than just being accessed through the internet via a browser.  Unfortunately, it no longer does as anyone who can figure out how to replace their clients with a browser and host their product will call themselves a “Cloud” provider.
  2. Contenders should stop using the term “Cloud” because it invites comparison with companies to which they are clearly superior:  Superior in terms of margins, market needs, architecture and strategic advantage.
  3. Pretenders should stop using the term “Cloud” for both ethical reasons and reasons related to survivability.  Ethically the term is somewhere between an outright lie and an ethically contentious quibble or half-truth.  Survivability comes into play when the company believes its own lie and stops seeing a reason to change to become more competitive.

AKF Partners helps companies create “Cloud” (XaaS) transition plans to transform their business.  We help with financial models, product approach, market fit, product and technology architecture, business strategy and help companies ensure they organize properly to maximize their opportunity in XaaS.

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The Problem with Non-Functional Requirements

May 4, 2018  |  Posted By: Marty Abbott

Many of our clients use the term “Non-Functional Requirements” to group into a basket those portions of their solution that don’t easily fit into method or function-based execution of market needs.  Examples of non-functional requirements often include things like “Availability”, “Scalability”, “Response Time”, “Data Sovereignty” (as codified within requirements such as the GDPR), etc.  Very often, these “NFRs” are relegated to second class citizens within the development lifecycle and, if lucky, end up as a technical debt item to be worked on later.  More often than not, they are just forgotten until major disaster strikes.  This happens so often that we at AKF joke that “NFR” really stands for “No F-ing Resources (available to do the job)”.

While I believe that this relegation to second class citizen is a violation of fiduciary responsibility, I completely understand how we’ve collectively gotten away with it for so long.  For most of the history of our products, we’ve produced solutions for which customers are responsible for running.  We built the code, shipped it, and customers installed it and ran it on their systems. 

Fortunately (for most of us) the world has changed to the SaaS model.  As subscribers, we no longer bear the risk of running our own systems.  Implementation is easier and faster, costs of running solutions lower. 

Unfortunately (for most of us) these changes also mean we are now wholly accountable for NFRs.  We now mostly produce services, for which we are wholly accountable for the complete outcomes including how our solution runs.

Most NFRS Are Table Stakes and Must-Haves

In the world of delivering services, most NFR capabilities are must-haves.  SaaS companies provide a utility, and the customer expectation is that utility will be available whenever the customer needs it.  You simply do not have an option to decide to punt attributes like availability, or regulatory compliance to a later date. 

The Absolute Value of NFR Your Product/Service Needs Varies

While we believe most NFRs are necessary, and non-negotiable for playing in the SaaS space, the amount that you need of each of them varies with the portion of the market you are addressing within the Technology Adoption Lifecycle.

As you progress from left to right into a market, the NFR expectations of the adopters of your solution increase.  Innovators care more about the differentiating capability that you offer than they do the availability of your solution.  That said, they still need to be able to use your product and will stop using it or churn if it doesn’t meet their availability, response time, data sovereignty, and privacy needs.  NFRs are still necessary – they just matter less to innovators than later adopters.

At the other end of the extreme, Late Majority and Laggard adopters care greatly about NFRs.  Whereas Innovators may be willing to grudgingly live with 99.8% availability, the Late Majority will settle for nothing less than 99.95% or better.

It’s Time to Eliminate the Phrase Non-Functional Requirement

We believe that even the name “Non-Functional Requirement” somehow implies that necessary capabilities like availability and data sovereignty can somehow take a back seat to other activities within the solutions we create.  At the very least, the term fails to denote the necessity (some of them legally so) of these attributes.
We prefer names like “Table Stakes” or “Must Have Requirements” to NFRs.
 
It’s Also Time to Eliminate the Primary Cause

While we sometimes find that teams simply haven’t changed their mindset to properly understand that Table Stakes aren’t optional investments, we more often find a more insidious cause:  Moral Hazards.  Moral hazards exist when one person makes a decision for which another must bear the cost:  Person A decides to smoke, but Person B bears the risk of cancer instead of Person A.

Commonly, we see product managers with ownership over product decisions, but no accountability for Table Stakes like availability, response time, cost effectiveness, security, etc.  The problem with this is that, as we’ve described, the Table Stakes are the foundation of the Maslow’s Needs for online products.  Engineering teams and product teams should jointly own all the attributes of the products they co-create.  Doing so will help fix the flawed notion that Table Stakes can be deferred.

AKF Partners helps clients build highly available, scalable, fast response time solutions that meet the needs of the portion of the Technology Adoption Lifecycle they are addressing.

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SaaS Migration Challenges

March 12, 2018  |  Posted By: Dave Swenson

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.

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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