There are many challenges when developing an organizational strategy:
- The process should involve as many people in the organization as possible, while still keeping the process focused and efficient
- It is often difficult to figure out which parts of a strategy are causes and which are effects.
- The resulting strategy needs to be simple enough that people can wrap their heads around it, but detailed enough to help people to choose priorities and measure progress
To address the third challenge, the SociaLens team typically works with leadership teams in organizations to produce a simple strategy map–a one page graphic that helps people to visually picture the organization’s entire strategy–as well as a simple process of measuring progress against the proposed strategy. The process is based on the concept of the Balanced Scorecard, a fairly well-known strategy execution tool that was developed and is used extensively by these folks. The first and second challenges, however, have proven to be harder to address.
We have been working hard on this problem, and we think we have at least a partial solution. It involves some of the stuff we know from our academic studies of network theory, crowdsourcing and wicked problems, and it draws on our practical experience with business strategy. Here’s how it works:
First we send out an electronic survey to as many people in the organization as possible.
The survey contains a set of generic organizational objectives and activities, drawn from a combination of traditional business strategy and the SociaLens digital fluency framework, that the participants assemble into a chain of six or less organizational goals and activities (if you would like to help us test out the survey, please visit it here). Each of these chains is a mini network of causes and effects. So in the graphic below, the goal of “improving lives..” is caused by “Improving product/service quality” caused by “Improving Product/Service Design” etc.
We store each of these mini networks in a database. A single mini-network doesn’t tell us a lot about what a potential strategy should be, but when 50 or 100 or 1,000 of these are combined into a big network thousands of connections they do.
You see, in any network, there are a number of mathematical measures that can tell you a lot about the properties of the elements within that network.
The first measure we use in our process is a simple count of the most-chosen objectives or activities. If 90% of the participants think that lowering costs should be the top goal of the organization, then it should be on the radar of the leadership when they are formulating the final strategy. Or if only one person chooses “Improve the Natural Environment,” then that should be on the radar as well. The more accurately that the overall strategy reflects these choices, the more easily that people will be able to align their efforts with it.
The second set of measures are more network oriented, and include things like degree or centrality which we can use to tell us which of the objectives or actions are the most connected to the others, or which are the most “important” in the network. Most often, the ones with highest scores are likely candidates for big goals, or for foundational activities that need to succeed if the rest of the strategy is to succeed.
So for example, in the network below created by five test participants (not really enough to get a robust result), the nodes with the higher “eigenvector centrality” scores are larger and more highly connected..
..which tells the strategy team that these are things that may be important for their organization to pay attention to when developing their strategy map. Additionally, the team might do some extra research into the connections between these key goals and activities to be sure they understand.
There is much more to this process that we will share after our initial prototype test that started on December 8, 2010. If you have not participated yet, please take 10 minutes to do so here. We will be writing more about the result in a few days.