//January

How brand-thinking can kill you, and capability thinking can save you

By |2015-01-29T19:12:50+00:00January 29th, 2015|Enterprise Architecture|

I guess it shouldn’t surprise me that business strategy work is often about constrained thinking.  Thinking “inside the box” is nearly always rewarded well.  After all, the person giving the rewards lives in the same box.  One of the most pernicious kinds of constrained thinking is “brand thinking.”  That is the notion that the value of your existing brand is the starting point for all your products.  Living within the box of the brand is definitely constrained thinking.

Brand thinking says “everyone knows us for doing this one thing well, so let’s invest in variations on that thing.”  That’s great.  And it often works.  For example, the Dell computer company has a great reputation for building good (but not wildly innovative) personal computers for individuals.  So naturally, when they decided to diversify, they decided that they should build on that brand.  They decided to build server computers for businesses.  It worked fairly well.  As they tried to become more innovative, they had problems with the brand.  In some areas, Dell simply bought other brands (Alienware for gaming computers, for example).

On the other hand, brand-thinking also leads to a kind of situational blindness.  Essentially, we choose not to see the things we think are outside the brand, or even the market, that we are used to.  And in doing so, we nearly always miss opportunities.  At least, until our competition points them out to us.  Dell was good at electronics manufacturing to the home.  Had they looked outside their brand, and focused on their abilities, perhaps in the 1990s, they would have been successful competing with Sony or Sharp for personal electronics.  Brand thinking says “no.” They stuck to computing, moving into printers, laptops, and tablets.  All have suffered from the “commoditization” of their market. 

A strategist is a unique role.  To be a successful strategist, you have to do everything you can to resist the boundaries of constrained thinking.  But then your ideas have to be judged by people who are PAID based on constrained thinking.  And that’s a tough sell.

Capability Modeling

When we do business capability modeling, we are looking not at the products of a company, or it’s brand, but at what that company can do.  We look at what a company has the people to do, the processes to do, the information to do, and the tools or technologies to do.  We bring together this knowledge into a complex model of elements, and summarize it as a capability map. 

The value of doing this is typically revealed when creating initiatives for the execution of strategy.  If a company is doing incremental strategy, there may be one or two areas that have slowed or prevented the company from achieving its goals with respect to its competition.  But when a company is following an innovative strategy, there may be a dozen different capabilities that need attention.  Some may have to be created from scratch.  Capability modeling is a clearly valuable tool in this arena.

However, there is another use for capability modeling that is not often discussed, and that is the need for unconstrained thinking on the part of the strategist. 

Could Capability Modeling have saved Kodak?

If you are over the age of 30, and live in a western country, you’ve probably heard of Eastman Kodak.  Known for their near monopoly on film and film processing, Kodak was the undisputed king of photography for decades.  In 1990, they held 90% market share.  They were unbeatable.  Remember this logo?  It was a very successful brand.

Let’s assume Kodak had done a capability model back in 1990 and had actually paid attention to it.  They would not look at their brand or their existing products, but at the things that they do very well.  What would be on that list of “things they do well?”

  • R&D in chemical-based manufacturing
  • Manufacturing of plastic and chemical based products
  • Manufacturing of specially treated paper
  • Manufacturing of chemical processing equipment
  • Consumer-focused marketing
  • Motion-picture-industry marketing

Let’s be clear here. These capabilities were not just solid.  They were the best in the world. 

What’s not on here?  Electronics.  Electronics manufacturing.  Electronics R&D. Electronics Marketing.  Not on the list.

So when Kodak started to see the need to expand, they used brand thinking.  People see the brand “Kodak” and think photography.  So why not go into the manufacturing of digital cameras?

Do you see anything on that list of capabilities that deals with innovation and manufacturing of digital cameras? Heck, they didn’t make that many analog cameras (Nikon, Olympus, and Canon made most of the analog cameras).  They had no distribution network, no reputation, no capabilities, no core skills to make cameras of any kind, and certainly not digital cameras. 

Even though they were able to leverage their brand for a while, eventually their ability to sell digital cameras fell away and they lost money.  Huge sums. At the same time that their analog film business was also losing money.

Now, look at that list again.  What do you see?  Ignore the fact that this is a film company.  Do you see other things there?

The simplest capability to build is the ability to market to a new segment.  The hardest is the ability to do R&D and manufacturing well, so let’s drop the marketing for a moment. Not completely, but let’s focus on the hard stuff.  Could they have built products based on treated plastics and treated paper?  Almost certainly.  There’s an entire industry that makes sheets of plastic film for a wide array of different purposes from glass protection to window tinting.  What about chemistry based R&D?  Could they have created innovative consumer products to compete with companies like Clorox or Proctor and Gamble? Could they have leveraged their chops in chemistry to compete with companies like 3M?  Maybe.  But only if they had looked first at their core capabilities.

The important thing to note about these industries is that they have not been disrupted by technology the same way that camera film was.  While these industries are not easy to compete in, the ability to leverage existing world-class capabilities is more critical to success than the ability to leverage the brand. 

Eastman Kodak thought of themselves in the film and photography business.  And it was their downfall.  Unfortunately, it still is.

And now a challenge…

What about this brand?  What are their core capabilities?  And what can they be doing with those capabilities? 

Are they on the precipice of disruption?  You bet.

American Express logo

Moving Towards a Theory of Enterprise Architecture

By |2015-01-16T13:28:41+00:00January 16th, 2015|Enterprise Architecture|

I’ve been asked a number of times over the years if I can explain the theory of Enterprise Architecture.  I decided recently to reopen that idea.  It’s not a new discussion.  I refer to Tom Graves post on the Theory of EA from 2012 where he posits that the theory of EA, if one were to be described, cannot be used to prove the value of an EA design.  The not-so-subtle hint is that there is, therefore, no value in creating a theory at all.  I disagree.  I believe that there is value in developing a theory of enterprise architecture. 

Let me first recap my gentle readers on what I mean by a “theory of EA.” 

Typically, in science, we start with observations.  Observations are objectively real.  They should be mathematical and measurable.  They exist within a natural setting and may vary from one setting to another.  We may observe a relationship between those observations.  The goal is to explain those observations in a manner that is good enough to predict outcomes.  To do this, we suggest a hypothesis, which is simply a guess.  We then see if we can prove or disprove the hypothesis using data.  If we cannot disprove the hypothesis, we have passed our first test.  We use the hypothesis to predict new observations.  We then check to see if the predictions are correct.  If so, we have a useful theory

Underlying Observations

Theories are created to explain observations and help predict new ones.  So what kinds of observations would I include in the Theory of Enterprise Architecture?

  1. The rate at which companies can adapt to change varies widely from company to company. Let’s call this the “rate of potential change” (RPC) because it refers not to the actual rate of change, but the potential rate of change which will never be less than the actual rate, but may in fact be more.
     
  2. This rate is important to the survival and health of a company.  Companies can die very quickly when their marketplace is “shocked” by a big change in customer expectations or competitive offerings.  If the Rate of Potential Change (RPC) is high enough, then any shock to the marketplace can be absorbed by an enterprise by responding competitively.  The cost of response appears to increase exponentially as time from the shock increases.  For example, from the date Amazon announced their cloud platform to the date that Microsoft produced a product that was as good as the Amazon initial offering, the time that elapsed created a steep obstacle for Microsoft to overcome.  The cost of overcoming that obstacle is much higher than if Microsoft had been able to respond sooner. The faster you can respond, the more chance you have of survival.  RPC measures how fast you can respond.
  3. The Rate of Potential Change (RPC) appears to be correlated with observable factors like the amount of alignment between strategy and execution, the quality and testability of company strategies, and the measurable maturity of key capabilities for absorbing and coping with change.

These observations need to be measured, collected, and validated.  And we need more observations to be researched, shared, and enumerated.  We don’t know quite what EA explains just yet, and building out the list of observations gives us a place to start.

The EA Hypothesis

At the highest level, the basic premise of Enterprise Architecture is simple:

The EA Hypothesis: The structure of and both intentional and unintentional relationships among enterprise systems has a direct and measurable influence on the rate of potential change and organizational cost of operating and maintaining those systems.

That simple statement is quite powerful. 

The EA hypothesis demands that we create a definition for “enterprise system” and a method for describing the “structure” of an enterprise with respect to those systems and to describe the “relationships” between them.  Clearly an enterprise system has to include socio cultural systems, information technology systems, workflow systems, and governance systems.    

The EA hypothesis suggests that the relationships between these systems are important.  That the relationships themselves influence the rate of potential change. as well as the cost to own a system.

The EA hypothesis demands that we measure the rate of potential change, and that we describe “organizational cost.” To do the latter, we must develop a clear idea of what is involved in operating and maintaining each of the included systems. 

The hypothesis is also fairly unbounded.  It leaves us with important questions to answer.

  • Can we cleanly and concisely define what we mean by “system” so that two architects independently examining the same enterprise would develop the same list of systems?
  • What are the types of relationships among systems and how do we differentiate relationship?  What attributes do these relationships have?  What attributes make sense?
  • Does it apply to one system?  A subset of systems? or can it only be truly understood to apply to the complete system-of-systems that is, in effect, a complete description of the enterprise?
  • What standard methods can we develop for identifying ALL of the relevant systems of an enterprise quickly and effectively for the sake of understanding the architecture of the enterprise?

I’m intentionally not answering these questions here because it is rational to leave all of these questions open for scientific research.  It is entirely possible that the answers may help us separate useful EA models from useless ones.  It is simply too soon to tell.

Why the EA Hypothesis matters

The rationale for creating an EA hypothesis is the requirement, often expressed through strategy, placed on an enterprise by its senior leaders, to do one of two things:

  1. improve the quality and reduce the organizational cost* of performing existing enterprise capabilities, or
  2. creating or expanding capabilities in an enterprise through targeted, specific and managed changes to the network of systems

This matters because nearly all strategy hits one of these two buckets.  This goes from corporate strategy all the way down to personal improvement: either you are improving your production, or your production capacity.  Either you doing what you know how to do, or you are learning new things.  Either you are getting better at the normal stuff, or innovating to add new stuff. 

Enterprise architects are called upon to help in both ways.  We have to answer questions like: “what does “innovation X” do for us, and what does it do to us?” We also have to contribute to ongoing concerns like “how do I grow my business in “Market Segment Y” in an innovative and compelling way?” and “How do I cut the cost of our IT expenditures?” and “How do I improve the quality of my customer data?”  These questions fall under the category of “organizational cost”.

* Cost and quality come together to include a balance of monetary cost, effectiveness, customer satisfaction, efficiency, speed, security, reliability, and many other system quality attributes.

We need a clear theory of Enterprise Architecture because answering these questions is difficult to do well. We have operated without a theory because we were able to “guess and check.”  We would guess an the scope and value
of an initiative, undertake it, and check on its value later.  But we are not able to say, in advance, that “proposed initiative A” is foolish compared to “proposed initiative B” because we have no science here.  It’s all just “guess and check.”

The term “guess and check” is not new.  My kids learned to use the “guess and check” method in elementary school math class as a way of exploring a problem.  But that’s where the “guess and check” method belongs.  Elementary school.  Grown ups use proven science.

All except EA.  We still use “guess and check.”  It’s time to grow up.

Next steps

  • First off, we need a long list of valid observations that we are trying to explain and understand.  The naturalists of a hundred years ago started with detailed drawings and descriptions of plants and animals and the habitats that they inhabit.  Perhaps we should start with detailed drawings and descriptions of the structure of different enterprises and the niches that they operate in.  We also need a valid way to measure and observe the “Rate of Potential Change” in an organization.
  • Secondly, we need simple reusable methods for conducting research in the area.  A consistent way to count and categorize systems, for example, and an accepted methodology for measuring their cost and quality that can be applied across different types of systems and companies.
  • Lastly, we need evidence of the cause and effect of making changes.  We need a solidly understood and measured system to be captured in a snapshot, and then a series of changes results in another solidly understood and measured system.  That gives us evidence of the value of the changes. 

 

Moving forward from here requires research. More on that connection in another blog entry.