Tool: Organizational Drivers

Complex organizations don’t abide by mechanistic rules or linear, deterministic systems, such as clock mechanism, for example. Instead, their dynamics inherently involve uncertainty and variability. While exact casualty does not apply, certain factors in the organization have significant impact on its behavior. These are called Organizational Drivers.

Identifying Organizational Drivers as well as their impact, is a critical task for every product development organization. Drivers are the key leverage points that can be either amplified or attenuated to produce some significant effect on the rest of the organization. While there are some relatively common drivers, many are highly unique and context-dependent. Generally, a driver can be any factor (a practice, a constraint, an actual person, etc.) that has significant impact.

Here are some examples of organizational drivers:

  • Marsha, influential senior Product Manager
  • Work-In-Progress limit at the cross-team level
  • Motivation of the team members
  • Metrics and KPIs
  • Encouraging stakeholders to drive the demo
  • Relaxing common cadence for loosely-coupled teams
  • Establishing common cadence for tightly coupled teams
  • etc… etc…

Not all drivers create positive effect! Some actually are the source of many problems (example: Reductionist Mindset, poor people management practices, Obsession with Metrics and so on).

Many important organizational drivers are Intangible by their nature and that is one of the reasons why they get often neglected or underutilized.

Drivers play crucial role in resolving systemic organizational problems and impediments. The following is an example scenario of drivers used in resolving a systemic problem:

Problem: team members overloaded and demotivated.

Drivers (based on hypotheses):

  1. Sugar-coating by middle management (negative driver; the hypothesis is that it contributes to upper management overloading teams)
  2. Linear perception of capacity (negative driver; hypothesis: this leads to systemic mismatch of capacity and load)
  3. Amount of scope, as a key success metric (negative driver; hypothesis: contributes to overload)
  4. Direct leadership involvement with engineers in problem-solving (positive driver; hypothesis: this will expose capacity bottlenecks and overload problems to the leadership)
  5. High-level WIP constraints (positive driver; hypothesis: such WIP limits will allow the organization to focus on finishing work)
  6. Customer involvement in demos (positive driver; hypothesis: this will expose problems with scope as proxy of value and will provide a more reliable leading indicator)

The change agents of the organization aimed at eliminating/attenuating the negative driver and introducing/amplifying the positive ones. As a result, it turned out that 4 and 6 produced dramatic impact; 2 required additional workshop with the leadership to practically educate them in flow in complex systems; 1 required a long time to make a cultural shift. Teams’ motivation gradually started to improve based on anonymous surveys. 

Here are some suggestions as to drivers in general:

  1. An organizational factor must be empirically proven do be a driver; without it it’s just a hypothesis
  2. A driver may be contributing to the outcome, but for reasons that are different from the assumed ones. In a complex system it is important to know not only how but also why something is working.
  3. The link between drivers and outcomes are complex and non-linear. Estimating exact affect of amplifying/attenuating a driver is generally counter-productive.

 

Ⓒ Org Mindset, LLC