June 5, 2024

Working with Bias in App Rat – Part 1

Introduction

Have you ever considered how your bias could influence your decisions? That your leanings could be steering you away from the most efficient course of action? This can be especially true when it comes to Application Rationalization (App Rat). In this first article of a three-part series, we will delve into how bias impacts App Rat, and why we need to be aware of this potential pitfall.

The Vulnerability of People and Teams

At the heart of any business are the people who keep it running. Their dedication and loyalty to the team, and their alignment with a specific vendor or tool, is often a strength. However, in the context of App Rat (or Application Portfolio Rationalization), this dedication can turn into a vulnerability. What if people become so attached to their preferred tool that they are reluctant to explore other, potentially more efficient or cost-effective, options? This is a classic example of ‘putting all your eggs in one basket'.

Negative Impacts of 'Experts'

Imagine a ship being navigated by a captain who insists on following one route, simply because they are familiar with it. This scenario resonates in the world of App Rat, where an ‘expert' on a suite or tool can steer the entire rationalization process. Their lack of objectivity and potential over-influence, perhaps even ignoring feedback from organizational Subject Matter Experts (SMEs), can severely skew the outcome. This bias can be a barrier to discovering better solutions, essentially, the ‘expert' is ‘missing the forest for the trees'.

Impacts of Unbalanced App Rat

Unbalanced App Rat, influenced by bias, can have profound effects on an organization. It can lead to:

1.
Inaccurate Evals

Bias may cause evaluations to be skewed, favoring one application over another without a fair comparison.

2.
Poor Decisions

Unbalanced evaluations can result in flawed decision making, potentially resulting in the selection of suboptimal tools or processes.

3.
Increased Cost

Favoring a more familiar but less efficient tool could lead to higher operational costs.

4.
Loss of Trust

Stakeholders may lose faith in the App Rat team if they perceive an ongoing bias.

5.
Resistance to Change

If the App Rat process is seen as unbalanced, employees may resist changes that arise from it, believing them to be unjustified.

Summary

In essence, working with bias in App Rat is akin to ‘walking a tightrope'. Maintaining balance and objectivity can be challenging, but the potential negative impacts of failing to do so underline its importance. By understanding how bias can make teams vulnerable, how ‘expert' influence can negatively impact the process, and the serious consequences of an unbalanced App Rat, we can start to formulate strategies to combat these biases, which will be the focus of our second part in this series.

Stay tuned for Part 2 where we will explore ways to reduce bias, and offer tips for working with developers, product owners, and product managers during the App Rat process.