In this series of articles, Kantar Employee Insights is exploring the challenges HR Professionals encounter when attempting to use data to inform employee engagement initiatives.
At Kantar Employee Insights’ most recent engagement workshop in Chicago, a HR Director from a retail organization was asked about the company’s continuous listening measures. He said they conducted routine New Hire, Engagement, and Exit Surveys. However, when asked how the organization links those three sets of data he simply said, “We don’t.”
His answer isn’t uncommon – less than 60% of organizations indicated they link the data from various surveys, and only around 10% of HR professionals feel that their organization is good at linking HR data to operational decisions.
Key findings from Kantar Employee Insights indicate:
- Four out of ten employees mentioned their organization does not apply HR data to operational decisions.
- Roughly 10% felt Strongly that their organization was good at applying HR data to operational decisions.
You can have all the data in the world, but if you are not effectively linking it (either to other data points or to organizational outcomes), your organization will struggle to achieve your goals. In this article, we explore some tips for linking data across surveys to provide a more complete picture of your organization’s performance when it comes to employee engagement.
Tip # 1: Include a few consistent items across all surveys.
When each of your surveys had unique items and questions, you cannot compare results apples to apples. It is important that you include a few consistent items across all surveys, such that you can establish linkages between results. As a best practice at Kantar, we encourage all clients to include the standard Engagement Index and achieve 60-70% similar items on their Onboarding, Engagement, and Exit surveys. This allows organizations to develop a strong baseline, and easily establish themes in the employee lifecycle.
For example, there was a specific division in a global manufacturing client where high turnover was occurring between the one and five-year marks. This turnover was costing the organization a lot of time and resources. After collecting a sufficient sample size and aligning the employees’ data from Onboarding to Exit, we helped the organization discover two key indicators for this turnover: Supervisor Effectiveness and Work/Life Balance.
Further, in a deeper review of the data, we found there was a six-month window where employees would get fed up and leave the division or organization. To fix the issue, the organization implemented a plan to Pulse Survey low performing managers every six months and continue to conduct their annual survey to reduce turnover and improve Employee Engagement. Without the data linking the surveys, we would not have been able to find this insight.
Tip #2: Start by keeping it simple.
Sometimes basic information can be the most compelling and easiest to understand. Consider conducting a Segmentation Impact Analysis. This very easy linkage analysis can be conducted in five steps:
- Align two sets of data. For example, Kantar Employee Insights recently conducted a study aligning the Willingness to Recommend Item with the Senior Leadership Item.
- Sort the data from highest to lowest in one column. For example, we sorted the Willingness to Recommend Item.
- Separate the data in four quartiles (See image below). Quartiles is a statistical term in which values are divided into quarters. Microsoft Excel has an easy equation to help separate the data using percentiles.
- Average each quartile and plot the four quartiles in a chart.
- Analyze the data.
In the example provided, we noticed there is a strong relationship between the Senior Leadership Approval Item and the Employee Willingness to Recommend Item. These results indicate that as the perception of senior leadership increases, the willingness to recommend increases. Therefore, it can be gathered that if organizations improve the perception of senior leadership, they will continue to improve the Willingness to Recommend Item.
Tip #3: Let your data do the work for you.
On my 8th birthday I remember receiving a new train set I really wanted. All my friends wanted me to open it up and I refused out of fear of scratching or breaking it. Nearly 20 years later I was visiting my parents and we opened the train set for the first time. It was so much fun and very much magical. I regretted not opening earlier.
This can often happen with data. Do not be afraid! Conduct a data audit, align, and follow the data noise because it usually leads to a compelling story. And remember you always have friends at Kantar to help you. If you have questions about linking the right data I would love the opportunity to help or even align you with our Statisticians and Data Thought Leaders.
To date in this series, we’ve examined tips for collecting the right data and helping you link data and results to outcomes. Next week, we will examine how to most effectively interpret the data.