Jan Bosch foto serie 1000×5633

Jan Bosch is a research center director, professor, consultant and angel investor in startups. You can contact him at jan@janbosch.com.

6 April

Humans are habit-driven creatures. Some research suggests that up to 95 percent of the day, the average human is purely on auto-pilot, executing according to the habits that have been built up over the years. Habits have many advantages, including not needing willpower to execute them, but of course, there are risks. The primary risk is that one easily gets stuck in operating in an activity-driven way rather than an outcome-focused way.

Once you’ve clarified your purpose (rule 1), the next step is to concretize this purpose in tangible, concrete and measurable outcomes. Failing to do so often leads to a major gap between what you say you do and what you actually do. An illustrative example is often found in startups. Every startup wants to grow its business, but translating that ambition into actual outcomes requires setting specific targets. Yesterday, I talked to a startup where the co-founder responsible for sales had a very concrete goal for the year: go from the current 4 paying customers to 26. You may debate if 26 is the right number, but it for sure is concrete and specific.

Speed, data and ecosystems

In his course “Speed, data and ecosystems,” Jan Bosch provides you with a holistic framework that offers strategic guidance into how you successfully can identify and address the key challenges to excel in a software-driven world.

Translating your purpose into concrete, tangible and measurable outcomes allows you to evaluate whether your actions and tactics are having the desired effect. For example, most companies want to shorten the time to market for new functionality. Specifically for functionality realized in software, doing more frequent updates in the field is obviously the way to go. Transitioning from yearly to quarterly releases, however, also means that release testing, updating documentation and all other activities related to a release have to be performed four times as often. Initially, many companies look to maintain the same, frequently manual, processes. Soon, however, it becomes clear that simply executing these processes faster won’t result in the desired outcome as the overhead is too high, people complain about the repetitive nature of the work, and so on.

When it turns out that the desired outcomes aren’t realized, the next step is to change your tactics. In our example, this means automating much of the work that’s now being conducted manually, so incorporating continuous integration and testing to increase the quality of the software well before the point where a release is scheduled. There are also tools for automatically generating necessary configurations of software, documentation, test case selections, and so on, that further limit the manual effort required to allow for more frequent releases.

If only a high-level intent had been expressed of shorting the time to market for new functionality, it wouldn’t have become clear that the current processes are insufficient. Instead, everyone would have complained about the difficulty of accomplishing things and the ways of working wouldn’t have changed.

One challenge I wrote about earlier is that we generally don’t control the outcomes of our actions. However, we can influence the outcome while allowing for other factors on which we have no influence. This means that when our actions and tactics aren’t resulting in the outcomes we hoped for, we need to assess whether this is caused by factors outside our control or our actions. For example, in stock market investing, poor returns can be the result of our selection of stocks and funds or due to a general bear market. The answer to this question can be easily answered by comparing your returns to a stock market index, such as the MSCI world index. If you’re doing worse than the index, it’s because of you. If not, it’s factors outside your control.

Translating a qualitatively defined purpose into quantitative outcomes is far from trivial. One of the challenges is that the defined outcomes often feel like approximations rather than accurate incarnations of your purpose. Here, the general advice is to follow the “perfect is the enemy of good” approach and allow yourself to start with some imperfect metrics. Once you’ve used these for a while, you start to learn where these work and don’t work. Following an iterative process, you can then, over time, come up with a better set of outcome definitions. Until, of course, you feel the need to redefine or adjust your expressed purpose.

I’m certainly not the first one to talk about these topics and several approaches exist for companies and individuals to use, including Hoshin Kanri and the Objectives and Key Results (OKR) model. The challenge, however, isn’t to pick the perfect system to follow but rather to sit down and translate your purpose into quantitative targets. For example, the Software Center for which I have the privilege to act as its director has the ambition to grow in size and impact. For 2021, the quantitative outcomes we’re looking to accomplish include adding two new partner companies and to double the number of social media connections we have on Linkedin, Youtube and Twitter.

Defining a purpose without connecting concrete, tangible, quantitative outcomes to it easily becomes aspirational without actual progress. Many have ambitions along the lines of exercising more, losing weight, eating better, and so on, without ever doing something about it and, consequently, never achieving the goal. Having clarified your purpose (rule 1) without clearly specifying the outcomes (rule 2) results in the same situation. Define a set of outcomes and, even if you’re far from satisfied with them, execute and iterate to improve over time. If done right, you’ll realize that you’re acting more and more in line with what you want your life to mean. Why settle for less?