Large Scale behavioral change: The Plause App Case study

1. November 2020 by Arndt Brandenberg and Roland Hess

Situation

Across businesses today, a continuous real-time flow of data can be used to gain operational insights, facilitating high-speed decision-making.

Take modern day Formula 1 racing: Among the top crews, the difference between winning or losing a race no longer lies in the drivers’ intuition alone. Victory is now achieved through making the right decisions in split seconds, aided by an enormous data stream from 200 sensors in the car being processed in dedicated server farms.

Based on these data and specific algorithms – derived from human skills and experience – a background team performs the small adaptations that, lap by lap, can make all the difference.

In business, this kind of process is being used across different industries, aiming to understand customers better
in order to provide them with the best products at the right time while boosting value added for the own enterprise.

But in one area this sort of knowledge has not been readily available as a basis for making decisions yet: The area with the most important assets of any company – its employees.

Complication

Across businesses today, a continuous real-time flow of data can be used to gain operational insights, facilitating high-speed decision-making.

Take modern day Formula 1 racing: Among the top crews, the difference between winning or losing a race no longer lies in the drivers’ intuition alone. Victory is now achieved through making the right decisions in split seconds, aided by an enormous data stream from 200 sensors in the car being processed in dedicated server farms.

Based on these data and specific algorithms – derived from human skills and experience – a background team performs the small adaptations that, lap by lap, can make all the difference.

In business, this kind of process is being used across different industries, aiming to understand customers better
in order to provide them with the best products at the right time while boosting value added for the own enterprise.

But in one area this sort of knowledge has not been readily available as a basis for making decisions yet: The area with the most important assets of any company – its employees.

Solution

One approach is trying to understand the mental models in an organization driving behavior and decision-making, uncovering any ‘blocking’ mental models.

Up to now, the standard approach is to run a number of ‘iceberg’ sessions. This widely used process is time-consuming; also, it only provides a snapshot view of an organization’s mental models. It doesn’t serve to represent a development.

A more valuable and sustainable addition to uncovering mental models would allow us to track improvement – and continuously measure changes in these models to see the impact of interventions performed within the organization.

Case Study

After a prototyping phase of PLAUSE, such a scenario was shown to the top management and respective teams of a PLAUSE client for the first time. The result: PLAUSE had uncovered parallel mental models to the team’s iceberg sessions.

One of the mental models coming up in over half of the iceberg sessions run was ‘I don’t have enough time to complete my tasks’, respectively ‘I need to complete things quickly’. This mental model leads to low quality, health and safety issues, and additional rework, again putting more time pressure on employees.

After deploying PLAUSE for ten weeks, the data created showed a very clear picture, placing the topic of available time in the low five scores for employee commitment drivers, and at the seconded lowest score when benchmarked to an industry peer.

So, excavating the issue of time as a key systemic blocking pattern from the data gained through PLAUSE has been corroborated by the results of the iceberg sessions – showing how PLAUSE could quickly dissect the truly underlying cultural issues in the organization.

Why is this important?

Dissecting these issues using longitudinal data the way PLAUSE does helps (a) building a fact-based narrative at the beginning of a cultural transformation, but more importantly (b) continuously measuring the value of interventions – just like in a Formula 1 race.

For leadership to be able to actually measure the immediate impact of transformational interventions – creates better options for reaction, adaptation and change in much shorter time cycles
– speeds up transformation
– allows to navigate more accurately in times of complex change.

In a nutshell

By using PLAUSE, leaders can focus their attention on areas, business units, and teams on an as-needed basis that can be provided from the data. Less time gets wasted on areas or teams that are already objectively performing according to a new, envisioned cultural setup.

This also allows organizations to pinpoint teams performing well with regard to the envisioned culture, acting as best practice examples. This will help to drive change via role models and boost the understanding and speed of large-scale organizational transformations.