An engineer’s take on improving productivity of knowledge workers: Part 2

In my last blog, I discussed how we can apply the cartesian method to take a structured approach to solving the complex and ambiguous problem of improving the productivity of knowledge workers. We also discussed the challenge of getting overwhelmed as we go deeper in the cartesian tree in search of precision and actionable insights.

Today, I’ll discuss how Systems Thinking can help us focus on the First Thing First. Let’s start with the 3 level productivity issue tree we constructed in the last blog.

Figure 1. First 3 levels of the productivity issue tree

Let’s imagine a situation where as the CEO you don’t believe that you have the right talent in place to deliver on the business strategy going forward. As Figure 1 shows, there are a lot of different levers that can be pulled to ensure that the ‘Right Talent’ is in place. It can be tempting to jump to the conclusion that this is a talent acquisition issue, or get into a whack-a-mole mode of trying to address the squeakiest wheel, or even end up in analysis paralysis because there are so many levers and they are all interconnected. This is where systems thinking can help us out.

For the sake of simplicity let’s start by looking at the Talent acquisition as a system. In Figure 2. the talent flows from Right to Left and it can be tempting to start ‘fixing the issues’ in the same direction i.e. start with sourcing; ‘let’s get more people with similar background as we have had success with in the past’. But the components on the right depend on the components on the left which means we would be better off starting the optimization in exactly the opposite direction.

Figure 2. Talent Acquisition System

We must start by clearly defining the talent profile that will help deliver on the business strategy i.e. what knowledge, skills, abilities and traits are needed. The selection mechanisms must ladder up clearly to the elements of the talent profile. The selection mechanism should be optimized for reliably and fairly evaluating those elements. Only then should we source people who meet the talent profile and are likely to pass the selection process. If we attempt to fix sourcing without the right talent profile and selection process we may : 1. find the right candidate but our selection process may reject them 2. find a candidate with a similar background as the right existing talent but they may not have similar competencies and traits as the right talent.

We can simplify Figure 2. by focusing just on the components we want to optimize and add similarly simplified views for the rest of the elements of the ‘Right Talent’. The overall system would look something like Figure 3. Now we know the order in which we should optimize the various components of the system and which downstream components need to be informed as we make changes.

Figure 3. Simplified view of the Right Talent System

Adding Systems Thinking on top of the Cartesian Method has reduced the likelihood of us getting overwhelmed by giving us an order in which we should proceed. But even then there is a question about which of these components need to be updated vs. not and how often do we need to repeat this process to stay on track. This is where we finally turn to math i.e. having the right ongoing measurements and analytics in place. More on that in the next blog…

My goal is to minimize guesswork and bias from people decisions at work