Advanced Analytics Improve a Customised Employee Engagement Survey: A Case Study
The Goal
Our global client had a custom-built employee engagement survey it wanted to replace or improve cost-effectively.
Scaling Up the Survey
Our client had expanded significantly since introducing a customised employee engagement survey years before. The engagement survey had always been deployed on paper because half the firm’s workforce was based in the field and had not been users of technology on-the-job. With tablets being introduced to the field staff and a much larger office-based contingent than previously, it made sense to bring the survey online.
Improving Survey Design
The employee engagement survey had been used several times with a relatively low total number of employees, meaning that advanced statistical analyses of the results had not been possible. With a larger workforce now in place there was the opportunity to improve the quality of the survey items and the report using advanced analytics.
Maintain a Familiar Survey
The employee engagement survey had been designed around the firm’s values and culture framework. The survey results had been used to good effect to reinforce the company culture and highlight areas for improvement. Abandoning their survey for an off-the-shelf employee engagement or pulse survey would mean the loss of that customisation and the ability to compare results over time.
The Solution
Roadmap for Improving the Survey
We created a roadmap for our client to improve their engagement survey and integrate it more with their HR data and analytics. The plan was to keep the core survey initially and create a clear transition path over time to a shorter, simpler, more data-driven survey and report.
Taking the Survey Online
Our Psychologists worked with our Data Scientists to recreate our client's existing survey in an open-source survey system hosted in the cloud. We could then feed the survey data directly into a customised analysis and reporting 'engine' we built for the client using 'R', the most common open source statistical programming language.
Analytics
The larger staff numbers meant that, for the first time, we could conduct more advanced statistical analyses to test the structure, validity, and reliability of the survey. We could also use analytics to determine what predicted engagement in different parts of the workforce - and what to do to improve engagement.
The Result
We started the client on a journey towards a highly-customised, evidence-based employee engagement survey with clear, actionable reporting.
Greater Insights into Engagement
The survey was able to provide evidence that what engaged the field staff was different to what engaged the office staff. Field staff engagement related to higher ratings of leadership behaviour and the importance of company values, whereas office staff engagement, was driven by having development opportunities and being in an innovative environment. The company had suspected that differences existed, but now they were able to be very targeted in the changes they made to communications and programs for improving engagement.
Flexible and Cost Effective
Although there was some programming required to customise the survey and build the reporting system, this meant the client was not wedded to any ongoing costs or to any expensive, proprietary software or supplier in future. If the company's values or other frameworks change, it's a relatively trivial task to adapt the survey - most Data Scientists could do it quickly.
Data-Driven and Actionable
The improved engagement survey structure was statistically valid and reliable. Our roadmap for the survey was proven to be on track. For the first time, the client was able to see which factors predicted engagement in different parts of the company. This meant they could confidently pinpoint the actions that would increase engagement for different employee groups.