Diagnosing and adjusting transformations to ensure success

This article is the third in a three-part series on applying systems diagnostics to understand the sources of organizational underperformance (Using systems diagnostics to drive process improvement and change), why transformations often fail to deliver (Designing transformations to avoid failure), and how to keep transformations from going off course (this one). It is based in part on my Strategic Analytics book. The issues addressed in the series will be covered in depth in the upcoming workshop Driving Organizational Change with Data.

The first article showed the details of conducting a systematic assessment of organizational performance challenges. The second article highlighted the importance of doing such an assessment before designing any transformation, to ensure problems with the current design are not perpetuated in the design of the future operating model.

The final risk, addressed here, is the uncertainty involved in rolling out the new operating model. If you conduct a systematic assessment of the new operating model soon after the change has been implemented, you will greatly increase the chances of successful transformation.

Diagnose and adjust the new operating model in real time

The details of how to do a systematic assessment of organizational performance challenges were laid out in the first article in this series. That has to happen as part of the transformation design process, well before any change is initiated. Doing so greatly increases the chances of surfacing and addressing the deep-seated issues in the new operating model design.

Yet conducting that singular assessment is not enough to ensure success, because of all the learning that takes place once the transformation is started. As detailed in my article “Building capabilities and changing the organization,” there is great uncertainty regarding how to do the work, and thus multiple learning curves to be climbed:

• Each person has to figure out how to do the new work, which takes time. People have different degrees of skills gaps, and are on different learning journeys.
• Simultaneously, teams are on parallel learning journeys. And the teams can only work everything out once each person knows how to do their part of the new work the right way.
• Because of all the uncertainty, there is an iterative process that constantly crosses the individual and team levels once the work starts
• The learning reveals that people and teams who were forecasted to be expert at certain tasks fall short in some areas, while others emerge as expert in unexpected ways. Which leads to adjusting how the work is done iteratively.

The best way to help the learning and adjustment process is to do a second systematic assessment of organizational performance soon after the change has launched. Doing so within a few months of the launch will turn up problems with implementing the new operating model that can then be addressed before they become embedded in the new ways of working.

Can the assessment happen later than that? Yes. However, the more time that passes, the more calcified the new ways of working become. Which makes it that much harder to correct behaviors and ensure we stay on path to an operating model and ways of working that deliver the strategy.

Most people will not embrace the change, and can hide behind the learning challenges

The learning process holds tremendous potential for upside benefit to the organization – while the uncertainty creates great downside risk.

The basic problems are that (a) people don’t like change, (b) the new work gets piled on top of what people already have to do, and (c) leaders too often do not take the time and energy to help their teams reprioritize where and how they should spend their time, and provide the support and resources needed to keep the workload from increasing. Given all these challenges, doing a systematic assessment of organizational performance can majorly help to overcome under-reporting of early signs of performance problems, and areas of passive-aggressive resistance:

Under-reporting of early signs of performance problems

• Many leaders do not encourage reporting problems with implementing the new design. They grow impatient with complaints about how hard it is to change, and believe that if their people would just work harder on figuring out the new ways of working, everything will sort itself out.
• So people hold back on raising any alarm bells, especially at the early stages of change, when things may seem a bit off target, but not yet at the point of the five alarm fire that cannot be ignored.

Areas of passive-aggressive resistance to the change

• Change efforts and organizational redesigns often fail, so the work then reverts back to what people were doing in the first place.
• This leads to conditioning among the old timers (longer tenured staff) that if they just wait long enough, the new effort will fail and they can happily go back to the way things were before.

Overload is a huge risk. Any substantial transformation means building new capabilities alongside or on top of the work that still has to be performed. Understaffing and task overload are often endemic, especially when there is great uncertainty over how to do the new work.

Overload happens because business leaders and finance don’t like to commit huge investment dollars until it’s clear exactly how many people are needed to do what. So they under-invest in adding people, until it becomes clear they have to. But by then they usually have demotivated their staff by making their lives harder than they needed to be during the change. That then exacerbates people’s unwillingness to be proactive in pointing out how to make the transformation be more successful: they long for it to fail so they can go back to what they were doing before.

Systematic assessments have dual use: to diagnose challenges before the change, and to guide the change to be more successful

Systems diagnostics like what I have advocated for here in this series can serve dual objectives. They can be used for up-front diagnosis before any change happens. And they can be used to guide and adjust the change in real time, to maximize the likelihood of success.

The two disciplines represented by these two approaches are analytics (upfront diagnosis) and organizational development (OD; making changes after launch). Various ways and benefits of taking this dual approach are explored in the upcoming workshop I will be leading with Maura Stevenson and Paul Taffinder on Driving Organizational Change with Data, which starts on September 24th.

First article: Using systems diagnostics to drive process improvement and change

Second article: Designing transformations to avoid failure