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Making data-driven decisions: How to turn organizational data into actionable insights

Making data-driven decisions: How to turn organizational data into actionable insights

As a customer success manager here at Nudge, I love numbers. Turning organizational data into actionable insights for the deskless and frontline organizations we work with feels a little like magic 🪄. Really, it is magic – we’re using the in-depth metrics our digital platform collects to predict product launch successes, check in on feedback and recognition programs, and gauge the overall health of organizations. We’re helping organizations make data-driven decisions every day. 

But how do we do it? Today, I’m taking you behind the curtain to learn how the customer success team at Nudge turns organizational data into those actionable workforce insights that organizations love for making data-driven decisions. 

When I think about workforce insights, I usually think about them in one of three buckets: 

Each of these three buckets provide a different range of insights – and require a different level of sophistication when it comes to analytics and workforce metrics. 

Before we get started, one quick plug: most of these metrics require a digital communication platform to truly tell a full story. While you might be able to capture some employee metrics from the more traditional deskbound channels (looking at you, email!), you won’t be able to get in-depth insights without a more robust platform in place. I can recommend a great one

Here are 3 ways to turn organizational data into actionable insights:

1. Check-ins

Why to use this: This approach comes in handy when you want to do a quick gut check on the overall health of your communication program, your feedback program, or your organization as a whole. Check-ins typically are static, looking at a metric at a given point in time.

How to use it: Gathering these high-level insights on how your organization is doing overall is easy – it’s great for organizations that are dipping their toe into workforce analytics. Here, I recommend doing weekly check-ins on your high-level metrics, like adoption rate and weekly active users. This shows you at a very high level how much of your workforce is using your communication and feedback channels – and, in turn, how much of your workforce is informed, empowered, and engaged. 

How to make these insights actionable: If you see warning signs in the data (like a sudden dip in active users), you could try one of the approaches below to get more information about the problem. On the flip side, if you see one region or location really excelling at, say, adoption rates, find out what they’re doing right – and replicate!  

2. Discoveries

Why to use this: Discoveries are great when you’re trying to answer a specific question, like “Why are my midwest locations seeing an uptick in turnover?” or “Are my teams ready for Black Friday?” Discoveries typically are static, looking at a metric over a period of time.

How to use it: Here, we start to get more sophisticated with our approach to analytics. To answer some of these questions (and unearth those sweet insights as a result), we need to go beyond a specific number and find trends in the workforce data. Typically, we would start with a check-in metric, such as knowledge rate, but dive deeper into the single metric. For example, if the goal is to determine the knowledge rate of our frontline on promotion X, here are some best practise questions to ask:

  • Are all locations scoring a similar knowledge rate?
  • Does the knowledge rate differ by region? 
  • Last year, did we see an increased or decreased knowledge rate?
  • Do the number of Nudges play a role in the knowledge rate of various locations?
  • Is there a correlation between Nudge activity and knowledge rate?

How to make these insights actionable: To get the most out of your discoveries, be sure to keep things focused around a goal. Workforce insights will provide you many data points to learn how your organization is performing. That said, it’s critical to select the correct metric that is aligned with the objective you are looking to solve. This process eliminates the noise and keeps the discovery hyper-focused on the task at hand. I’ll often be looking at goals around content performance, execution, and recognition, for example. 

3. Reports

Why to use this: Here’s where we start to get into larger data sets that provide a more fulsome look at the health of an organization. Reports typically are typically dynamic, looking at a metric over a period of time (and often pull in other data outside of Nudge)

How to use it: When I’m taking this approach to workforce insights, we’ll pull specific numbers from our Nudge Analytics dashboards to build larger in-depth reports that can be customized and manipulated by an analyst. For example, if we wanted to create an “Employee Engagement” report, we might be pulling numbers related to everything from adoption and usage to knowledge retention and campaign execution. 

How to make these insights actionable: We’ll often use our segmentable dashboards to compare subsets of an organization in these larger reports, to see where learnings arise. As with Discoveries, a similar insight logic would hold true when turning Reports into actionable insights. The key with Reports is that we look to leverage the best data available to build the strongest picture of a specific organization. This typically would involve combining your workforce data with some type of data outside of Nudge, such as sales or retention data. This synergy of data allows companies optimize the various business drivers with the frontline and in real time test the impact it has on the broader business 

Other tips on turning data into insights (and making data-driven decisions!)

Beyond these three approaches, I wanted to share a few more tips and tricks for finding actionable insights and making data-driven decisions: 

Look for patterns. Does X region always score lower on knowledge campaigns? This could signal something larger at play.

Keep focused. Folks can often try to improve many metrics at once, but this can lead to information overload. Growing awareness, for example, is much different than increasing the knowledge rate of your frontline.

Listen to your frontline. Combine the quantitative aspects of your communication strategy with qualitative data to build a holistic approach to communication. 

Don’t be shy. Your frontline is always eager to share and provide their honest feedback. A not-so-nice metric always provides the foundation for improvement and growth. 

Correlate Correlate Correlate. Combining workforce data with any other company data allows for greater analysis and insight into the business drivers at that time.

Use your own benchmarks. When looking for red flags, nothing beats your own company benchmarks. It can be really tricky to try to compare your metrics against industry norms, especially with so many industries in turmoil at the moment. 

Use organization data to check on your onboarding programs. We all know that a successful onboarding program is crucial to the success of new hires – and with the labor crisis raging on, who can afford to lose new hires? Depending on how sophisticated your onboarding program is (we recommend a trigger-based system within your communication platform to keep it timely and responsive), you might be able to identify what is working and what is not when it comes to your onboarding process – and even compare these numbers against your turnover rates to uncover more insights. 

That’s it! I hope these tips help you to find the actionable insights you’re dreaming of. Just stay focused and look for patterns, and you’ll be making data-driven decisions in no time!