Organizations do not work, in real life, like they work on paper. On paper, there are departments (all shaped like a neat rectangle) and business processes with neat inflows and outflows of responsibility and information. On paper, you improve things by modeling things on paper, and then moving things around, on paper, then teaching people to follow the process that your neat paper diagrams represent.
In real life, there are human beings and the tools that they use. Sometimes the tools move information from one person to another. Sometimes, they just aid in communication. People meet and get to know other people, and they learn to trust some, and distrust others. Some folks have different measures and motivations and just “pass by” one another. Some subset of these people will have shared cultural values and expectations. There may be many cultures in an organization: both because the organization is in multiple places, and because people from multiple places join an organization. Also, “business culture” arises as leaders achieve successes and people learn to use certain “cultural expectations” to get things done efficiently.
Reality is a lot messier than pretty rectangles.
Enterprise Architects apply science and engineering and aesthetics to the challenge of organizational change. We are unique in that most other “change artists” are not focused on engineering and some even ignore science. (see Daniel Pink’s TED Talk on the Surprising Science of Motivation). Few even know how to spell aesthetics. Yet, when you are dealing with systems that contain and include people, you have to use aesthetics, and you are ill prepared for success if you ignore science. Engineering is a mindset as much as a class of methods. It involves applying the things that science has discovered and using that understanding to build great (and sometimes terrible) things. Engineers build on ideas and use them, often experimenting on systems that are too complex and intertwined for “pure science” to get arms around.
As Enterprise Architecture is such a young science, we have relied to heavily on the “boxes and lines” model of enterprises, and not enough on the messy but important sociocultural view of an enterprise. We find it easier to document, and model, and even simulate, processes as though people were interchangeable and their relationships didn’t matter.
That is just lazy.
It is time to get up off our collective butts and start working out ways to understand sociocultural influences, relationships, and architectures. We have to build ways to detect, measure, and consider these structures when we measure capabilities, or improve processes, or suggest automations, or evaluate business models, or any of the two dozen things that EA’s do.
The value of EA often comes to an executive in the form of a reasoned opinion that is based on data that no one else is looking at. Let’s consider the possibility that examining sociocultural influences can provide interesting opinions that an executive will find valuable.
We should consider sociocultural information if:
Think about it. Do you believe that any of those statements are false? I can find ample examples for each one. So if sociocultural interactions matter, why are we not tracking them, learning from them, using them to make decisions?
It’s only hard because we haven’t tried.
(This post inspired by the many similar pleas shared by J.D. Beckingham in social media).