Case Study: Increasing Tool Adoption with Data-Driven Change ManagementCASE STUDY
If there’s one thing we know, it’s that virtually every decision is better when we have data to support it.
As vital as change management is to organizations today, it can not be an exception to the data trend. The famously “soft” function of HR is now enhanced with advanced tools and methods for more informed, data-driven decision-making.
Our Organizational Assessment 360® has been an invaluable tool in helping companies quantify the impact of change efforts on the organization. Here is an example of how we applied analytics to significantly improve adoption of a new tool at a multinational technology company.
As a result of excessive service calls and lengthy call times, customer satisfaction had plummeted over the past several years. Our client discovered that poor data quality was to blame for the inefficiencies of his service center. Thus, he initiated an enterprise data governance program and implemented a new tool that involved a significant impact to processes across functions. However, adoption of the new tool was low and customer data quality remained poor. We were brought in to increase enterprise-wide adoption of these changes and employee engagement around the initiative.
Implementing a data-driven culture change across the enterprise was complex because of the different business units, functions, and roles that each had their existing processes.
From a change management angle, our main questions were:
1. How can we maximize adoption across regions and functions in the shortest time possible?
2. Which areas of the organization did we need to target specifically as potential “bottlenecks?”
We used operational data, engagement data, as well as employee survey data to develop a statistical model of the factors impacting tool adoption. We realized segmentation would be necessary early on due to the high variation in the base of 55,000 employees.
|| With tool use frequency as the dependent variable, we were able to see relationships between employee satisfaction, company tenure, and functional unit.
Unsurprisingly, the data showed a clear link between tool adoption and overall employee engagement across segments. However, different communications and training strategies seemed to work for different segments of employees. For example, on a whole, US based teams seemed to engage most after in-person workplace events. On the other hand, Asia-based teams engaged the most after weekly e-learnings and quizzes.
We also saw a general trend that employees who had been at the organization for 15+ years lagged in tool adoption utilizing our existing strategy. We hypothesized that this was due to a culture transformation, which had brought in a high proportion of millennial employees. Furthermore, company-wide communications in recent years had mostly targeted newcomers/younger employees. Particularly older employees working in functions more driven by order and predictability reported feeling “overwhelmed” and “overlooked” with the constant pace of change. We realized from this data that current strategies of increasing tool adoption were not hitting the mark with a high percentage of employees.
Looking at this data, we were able to help our client modify communications and learning approaches, as well as redirect resources to target specific segments that needed more support:
- We tailored communications and training strategies by region and age group and continually optimized the mix of strategies used.
- In addition to standard company-wide trainings, we designed a tailored in-person training strategy for groups that were lagging in adoption. At set hours during the week, trained assistants came around the floors and provided hands-on, one-on-one assistance for employees who requested this service.
- We advised company branding and communications to appeal to a more diverse age base.
The data allowed us to see the effectiveness of different change management strategies across the enterprise. We could then optimize the change management budget accordingly. We also saw that an important segment of employees was being left behind in our change management efforts. Thus, we needed to employ a different, more personalized strategy to reach them.
Our client was able to significantly raise tool adoption rates and data quality within 6 months. As a result, by the end of the year, our client significantly reduced both the volume and length of service calls, improving overall customer satisfaction.
Want to increase your organization’s ROI using data-driven change management? Learn about our change management tools and how they can help you achieve your objectives.
– Rik Nuytten, EVP, Information Strategy at Cisco
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