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How Customers Use Your Technology

When we build products we spend a great deal of time and effort thinking through how our customers will use them. From all this effort we believe that we full understand our customer and system interaction. The reality is often that we don’t know how customers will ultimately decide to interact with our system. An example of this is how social networking sites were originally intended for people to meet and interact. Soon after the launch of Friendster people began setting up accounts for their pets. This came to the attention of Friendster’s management and they began shutting down these “fake” accounts. This, as you can imagine, upset many of these individuals who thought their pets deserved to experience social networking but the point is that customers had decided to utilize the system in a very different manner than the company planned or even approved of.

The academic research that can be used to explain this phenomenon is adaptive structuration theory (AST), adopted by DeSanctis and Poole from Anthony Giddens’ theory of structuration. AST describes structures and agents, where there is a duality of structure  that exhibit an interplay between the structures inherent to advanced technologies and those that emerge in human action with these technologies. Orlikowski also extended Giddens’ work into technology by examining how people enact structures as they interact with a technology that affect their use.

Back to our example of pets having their own accounts on social networking sites. Customers are going to adapt their usage of our technology based on our product’s design as well as their interactions with the product. Our responsibility is not only to focus on the customer during the conceptualization, design, and development phases of our products but also in the maintenance phase. Take note of how the products are really being used by our customers in order to not only support their use but leverage it for further product refinement.


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Data Driven Decisions

By now most of us have heard concepts such as the wisdom of crowds or A/B testing but still so often we make decisions without gathering data. Admittedly not every decision we make during our busy days requires data analysis but the ones that matter such as your product’s UI redesign, a price change, or advertisements often get the same treatment as your choice of lunch sandwiches. Perhaps you or someone on your team claims such connection with customers or product expertise as to not require testing. Don’t believe this!

Allow me to share with you an antecdote from my past that shows differently. Some of the facts of this story have been obfuscated to protect intellectual property but the gist of it remains true. The company that I was working with sold a product that allowed customers who purchased it to receive a return on their investment in a variable amount of time depending on how they configured the product. When getting up to speed on the product I asked everyone from the CEO to customer account managers, many who had been working with in this field for years, which was the optimal configuration. Everyone suggested a particular configuration. Being a bit of a stats geek from my days in Six Sigma I grabbed some data and started analyzing. The initial results shocked everyone because they indicated the exact opposite of the “optimal configuration”. After a complete A/B test the company ended up building a practice and product around the new ideal configuration, a big win for customers.

Ian Ayers in his book Super Crunchers offers several examples of random testing from companies as diverse as Monster.com to Capital One that have resulted in tens of millions of dollars of increased revenue. Companies such as Offermatica and Google offer A/B or even multivariate testing. Ian actually used this same techinque through online advertisements to determine the title of his book. Tim Ferriss in his book Four Hour Work Week did something very similar and recommends this approach to quick testing with advertisements for everything from business ideas to homepage redesigns.

While we caution against analysis paralysis there is a middle ground. Our mantra for processes is “Right Time, Right Process” meaning you need the process that fits best today for the your team and for the task. As we state in The Art of Scalability “Each and every process must be evaluated first for general fit within the organization in terms of its rigor or repeatability and then specifically for what steps are right for your particular team in terms of complexity.” The bottom line is, for decisions that matter get the necessary amount of data to make the best decision.


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Product Design – Flexible is Fat and Omnipotent is Impotent

I’m a huge fan of Marty Cagan’s book and blog.  His most recent post on “The Domesticated Computer” got me thinking about how and why so many products not only take too long to develop but fall so short of user expectations.

I’m convinced that we have a nasty habit of attempting to launch products in all phases of development, and especially in the initial product launch, that simply do too much.  While we’ve all heard of the Pareto Principle, it seems that we just don’t apply it to our product development efforts.  Far too often we find ourselves in product discussions that look more like congressional pork barrel politics.  Features are negotiated based largely on executive pet projects than structured methodologies like Moore’s Whole Product Concept.

As Marty C points out, the personal computer, with all of its flexibility, is still difficult to use in many respects.  In the mid 90s I ran a project at Motorola that took computer keyboards off the manufacturing floor in favor of a yes/no device.  While the activities of the manufacturing line stayed largely the same, productivity increased.   Users indicated that the system was simply easier to use.  Nothing changed in terms of keystrokes – only one was still needed.  But less was better and faster.  More was fat and impotent.

Contrast the PC with purpose built systems like the iPhone, iPod, iPad, Kindle, etc.  The latter devices all have relatively limited primary input mechanisms.  Sure some of them have keyboards – but they aren’t the primary means of interaction.  More importantly these systems are designed to accomplish a subset of tasks as compared to the computer.  This limitation in functionality allows for better interaction characteristics and less user confusion.  It’s a lot easier to design easy to use systems if the system being designed only needs to flip pages and perform searches or scroll through and play music.  As my partner Mike Fisher points out, there are probably reasons why kitchen appliances still largely do one thing rather than a combined fridge/toaster/fryer/baker/washer.

But what lesson does this have for us in designing web applications?  Less functionality leads to less confusion, easier interaction development and faster time to market.  Develop the 20% of functionality that will deliver 80% of your revenue and refine it until its perfect using multivariate (or simpler A/B) testing.  Speed and focus is so much more important in web based properties, especially in early releases, than breadth and depth of functionality.  The folks at 37 Signals say that you can always do less.   Our point is not only that you can do less, but that you SHOULD do less.  Less is faster.  Less will allow you to get the core functionality out and perfected quickly.  Less wins.


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How to Deal With Unintended Consequences

Having just read Levitt and Dubner’s SuperFreakenomics as well as Tenner’s Why Things Bite Back, I’ve been thinking lately about unintended consequences, sometimes referred to as a “law of unintended consequences”. As defined by Rob Norton, it is “that actions of people – and especially of government – always have effects that are unanticipated or unintended.”  Norton sites the reference to unintended consequences to luminary economist and social scientist such as Adam Smith, in his “invisible hand” that self regulates markets, and John Locke, in his campaign against the 1692 legislation for limiting the maximum rate of interest that could be charged.

In Tenner’s book he covers a variety of topics including environmental, medical, and technology advances that have caused unintentionally problems. He uses the term “revenge” as in these advances have taken revenge on those who initiated them. What interested me was not the “revenge” but rather just our inability to predict accurately the outcome of our actions. All of the examples appear to be complex systems, meaning that the exhibit behavior not obvious from the properties of their individual parts. As much as we understand about the human body there is at least an equal amount that we do not understand. The same goes for our environment. Argue with me if you will but when the accuracy of a 7-day weather forecast is less than 50% (using the meteorologist standard of temp predictions within 3 degrees as accurate) or 85% accurate for precipitation 1 day out, it is hard believe that we have a great understanding of the earth’s climate and weather systems. Perhaps you can make a case that on a micro-scale we’re inept but from a macro-perspective we know what we are talking about.

When we add to our Software as a Service or Web 2.0 sites our human customers then I believe our systems start to take on attributes of complex systems. If we could accurately predict the human-computer interaction of our system then we would find all the bugs in our next release in QA. Unfortunately time and time again we learn of bugs or unintended consequences such as a huge drop off rate in sign-ups only after the release after it goes live and real people start interacting with it.

Why we fail at predicting human behavior or weather patterns or any number of other subjects is too broad for a post. However, with the knowledge that we will fail, we can take actions to minimize the impact of the results. The way to achieve this is through A/B testing or split-testing. If you approach changes in your releases as if you’re just as likely to reduce some desired behavior as you are to improve it, you’ll want to have a way to test the results in the real world before committing to them. In our practice we often tell clients that they should have an A/B testing framework or a wire-on/wire-off framework for a variety of reasons including risk mitigation for new features. In today’s world where there are free services that can help with this such as Google’s website optimizer, here is a great case study of how to use it, there really is no excuse for not having this ability within your site or service.


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Initiatives That Kill

In a recent post Marty talked about false urgency being terrible for the performance, morale, and well being of a company. I’d like to add to this the wasted time, energy, and money on “initiatives”. Similar to how creating a false sense of urgency leaves the employees unmotivated and ridiculing the project, initiatives that do not support the mission of the company produce the same effect.

As an example of what I mean by “initiative” let me relate a project that was undertaken recently by a large corporation. In a cost reduction effort someone was assigned to walk around and patrol the office area for plugged in electronics and appliances. In my mind this is just ludicrous. First, the company has hired people they trust to build their product or systems.  If the company wants to initiate a cost reduction plan to reduce the electric bill, send a note out to the employees asking for their help. A much better approach is to demonstrate that you trust that they will help with reducing costs. Second, my bet is that the time wasted by this person patrolling the area, some manager monitoring and reviewing the patrols, and the other employees making fun of this cost the company more than it was able to reduce. And third, the company should weigh the cost of possibly having to replace a single great employee against the cost savings of such initiatives.

This example provided seems to be pushing to an extreme the silliness boundary of what someone can dream up under the guise of cost reduction but fails to interpret the further ramifications. Looking at just the balance sheet or income statement fails to take into account the wasted time by employees and aggravation over such imposed bureaucracy. Another clear sign to me of a company that is focused on the wrong things is when purchases must be performed through a centralized acquisitions organization. I understand and agree that there is no need for every department to negotiate a cell phone plan but when the IT department must involve a non-technical purchasing agent to whom they have to justify the purchase and allow that person to negotiate with the vendor, things have gone overboard. There is no reason that managers shouldn’t be given authorization for purchases up to various amounts and escalations going, not outside of their department, but just to their boss.

If you’re in an organization that has implemented these initiatives you should take the true pulse of the organization and see if you don’t come to the same conclusion. Working on these bureaucratic initiatives are likely costing you more in productivity, creativity, and deliverables than whatever amount you are saving.


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Perception is Reality

We’ve all heard that saying “perception is reality” but do we really believe it applies to us? We all probably think we’re competent at our jobs but being so is only half the journey. We need to demonstrate that competency to our peers, employees, bosses, and customers in order for it to matter.

In good counseling sessions we should receive some praise for what we’ve done well and some feedback for areas that we need to improve. My advice to people receiving feedback is first determine if it is factual. Do you really write poor quality code? Are you actually tough to work with? If you believe the feedback is not factually correct, don’t become defensive and try to refute it because the blame is still yours! Even if the facts are incorrect but your peers, boss, or customers perceive them to be correct, you own this perception.

People usually hate to hear this and think they should just have to focus on their skills and everything will work out but the reality is that you need to own people’s perception of you. The same goes for customers. You cannot just focus on building a good product and assume customers will flock to you. You have to own your customers perceptions, which means you have to consider not only the quality of the product but how you introduce the product, how you roll out the code, how you perform maintenance on it. All of these ultimately result in your customer’s perception of the product, not just the number of bugs.


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To Succeed Big, Think Small

I, like a lot of you, read lots of blogs and articles each week, some of my favorites include Joel on Software, Coding Horror, High Scalability, Seth Godin, and Tim Ferriss. I also read just about cover to cover the IEEE publications that I receive. I use a variety of methods to keep track of the ones that I like so that I can find them easily when I want to reference them. Two of my favorite tools to do this with are Evernote, where you can clip web pages with tags into your notebook, and ShareThis, where I can drop something in my sharebox and send it to someone at the same time.

I was having a discussion the other day about small services as business opportunities and recalled several threads that seemed to be tangentially related. I parsed through my clipped, starred, and shared items and found these pearls. Whether you are already part of a start-up or considering one here are some ideas that you might consider.

And since one of the technical editors of our book has pounded into my brain the demand to “explain how this relates to scalability”, let me explain. If you’ve read a few of our posts you know that we believe that scalability is about more than technology, in fact if done correctly it’s technology agnostic, but depends greatly on people, process, and architecture. This starts even before the business is founded. The right business plan that balances people and investment with real revenue earning products is critical to scaling. If your cost are too high to service a given number of customers you are losing money. Now you can argue that you’ll get efficiency of scale at some point but you need to survive long enough for that to occur. Without further ado, on to our amalgamation of advice:

Seth Godin says the way to make money on the Internet is by connecting people with what they need. He gives examples that include the following as well as many more:

Connect advertisers to people who want to be advertised to.
Connect job hunters with jobs.
Connect information seekers with information.
Connect teams to each other.

Kevin Kelly says the solution for inventors who are up against the giant aggregators like Amazon is to find 1,000 “true fans”.  If each one is willing to pay $100 each year for something that you invent or service that you provide you can make a great living. This might be four CDs that you produce each year. For those organizations comprised of more than just a solo artist, Kelly states that an increase in fans is necessary but is linearly proportional to the increase in the team size.  He continues that because of the network effect (Metcalfe’s Law) it is likely that the value of the your fans increases proportionally to the square of the number of fans, which means the number of true fans does not have to double to support a duet.

Paul Buchheit, the 23rd employee at Google and creator of Gmail says stick with it, overnight success takes a long time.  They started Gmail in 2001, launched it in 2004 and 7 years later is seen as a huge success with annual growth rates of 40%.

Matt from 37Signals advises to keep your day job and work on your start-up on the side. Even though he capitulates that starting a business does require plenty of time and effort, quitting puts a shot clock on your idea. When coupled with Buchheit’s notion of success is a measure of endurance not speed, this seems like sound advice when possible. For those already under the pressure of the shot clock just remember that is monetization is king and survival is a competitive advantage.

So far in our bucket of advice we have 1) connect people with what they need, 2) find 1,000 fans to support your dream, and 3) don’t jump in until you are able to stick with it for the long haul. What I can add to this is Think Small. Throw away the fifty page business plan that requires $25 million of investment to sustain a profitless company for seven years. Instead think of a single service that people or businesses need.

For Internet companies, there are dozens of services that they need as part of their product offering but only as a small part.  Therefore they either don’t have the expertise or they can’t dedicate the resources to build it well. An example of this is search. Lots of websites need search functionality but few are going to build it themselves when there is a site search tool built by experts available.

Services that come to mind and that either need to be done or need to be done better are contextual classification, yield optimization, micro-payments, recommendations, abstracted scaling, and application monitoring. Go give it a shot and think about scaling from day one of your business.


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Advertising Revenue

The Internet Advertising Bureau (IAB) just released Q1 revenue numbers for advertising online which showed a 5% decline over the same period in 2008.  At $55 Billion in advertising revenue for Q1 2009, the amount is equal to 2007 revenue numbers. “Interactive advertising has taken its rightful place as a fixture on marketing plans across sectors, which means we aren’t immune to broader economic trends,” said Randall Rothenberg, President and CEO of the IAB.

David Silverman, PricewaterhouseCoopers Assurance partner, stated “Current economic conditions are clearly challenging … nonetheless, interactive media continues to consume a larger piece of the overall advertising pie.” According to the growth rates of advertising display mediums, internet display ads were growing at 7% year over year from 2007 to 2008 while all other mediums (radio, newspaper, magazine, outdoor, etc) were shrinking, except for television which grew at a modest 2%.

As we pointed out in our post about monetization, we don’t necessarily believe that people are resentful of advertising on free services or that this downward trend is anything more than online advertising being tied to the economy. However, if you were a start up planning on starting monetization through advertising in 2009 this economy and downward move of advertising spend might have caught you at a particularly bad time. Had your business model built in profitability from the start, you would not be immune from the economy but you would be able to react quicker and be impacted less. Amassing a following and then figuring out how to make it into a business is a great way to burn cash for a lot of years.

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Art v. Science in Products

Bringing compelling and unique products to market requires a blend of art and science.  The art is the vision of what might be; the stirring promise of something that might change our lives or make it easier, faster or less costly to perform some function or task.  The science is the practical implementation of that vision; the profitable development, manufacturing and deployment of the product in a manner that is accretive to shareholders.  In our world, product vision embodies the art of what’s possible the science of the practical is defined by architecture, design, discipline and execution. 

 

Sometimes the intersection of what’s possible and what is practical is narrow or non-existent.  In the case where it’s nonexistent we should run, not walk, away from the idea as very often it is destructive to shareholder value.  Where that intersection exists but is small we should tread carefully to build something that can create shareholder value and hope that the foothold we create can expand once technology advances giving us a first mover advantage. 

 

But what about when there is a larger intersection?  Which is more important, the art or the science?  While there are many people who will take one side or the other, and while I have my own opinion, the best answer is that you need both.  Rarely is it the case that you will find someone with a compelling product vision and incredible execution skills as these two things seem to sit on opposite sides of a spectrum. It is much more likely that you will find someone who sits in the middle of the spectrum.  These people can paint a vision and execute against it, but they aren’t Steve Jobs on the vision side or Jack Welch on the execution side.

 

We think some of the best teams are built with two people and potentially two organizations embodying the art and the science.  A natural conflict occurs here, but it needn’t be an adversarial conflict.  Assuming the appropriate company culture and a healthy respect for each other’s abilities and value-add to the company, it is possible for these people or organizations to work together and for the healthy tension to accelerate the creation of shareholder value.  The “science” tethers the “art” and keeps it from wondering off aimlessly with no clear implementable path to value.  The art buoys the science and keeps it from sinking and being mired for a lack of product differentiating vision.

 

As chief executives, it is our responsibility to attract and retain “the best of the best” within both the art and the science and to create a culture where both are valued.  We should reward the folks who think and appear to be lost in the clouds to the same level as those who are attempting to keep them anchored to the practical.  Neither should be seen as less or more important and the debates between them should be cordial and filled with mutual respect.

 


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Attention Detroit: Use Technology to Save Your Company!

We have for far too long relied on a “make to stock” model for the automobile industry. In essence, car companies attempt to predict user demand when scheduling cars to be built through their factories and then shape the resulting user demand to what is actually in stock at the auto dealers.

If our automobile companies had instead relied upon a build to order model, they may not have found themselves asking for billions in bailouts or on the brink of bankruptcy. They would not, for instance, have overproduced the large gas guzzling SUVs that have remained piled up at dealers. When gas prices increased, orders for these vehicles would have fallen and the car companies would have shut down production on them. Jobs would likely have been lost much earlier, but the companies likely would have been in a better position to weather the financial storm.

A 2002 Forrester Research report indicated that “The auto industry’s failure to align production with customer demand costs billions each year”. Why don’t we demand a fundamental shift in business model with some of our taxpayer money? Some things are just too obvious…

Detroit – here’s an idea: Hire a couple executives from Dell and use some of the bailout money to switch from demand forecasting and factory planning systems to built to order “configurator” systems. Dealers can still stock some cars for people to test drive and maybe even purchase, but most sales can happen electronically. Everyone wins. You stay in business, dealer margins increase (they need to stock fewer cars), customers get what they want – not what they are sold, etc. Yes, we might need to wait a couple extra months to get that new car but maybe, just maybe, you’ll be in business for another 10 years.


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