SAP SuccessFactors Reporting & Analytics: 5 Do’s and Don’ts

Imagine that you work in a bakery called SAP SuccessFactors, and you’ve spent months, or maybe even years baking a near perfect cake (aka implementing your HR solution). You can consume the cake as is, but what’s cake without frosting? Think of reporting & analytics as the frosting that makes your cake that much more palatable. The goal to implementing any HR technology, after all, is to ensure that your organization is consuming the data and insights to make more informed decisions.

Well-developed and effective reporting and analytics can help you achieve that goal, but it can also have an adverse effect and leave you in a state of “analysis paralysis.” You know, the feeling of analyzing so much data you just don’t know what to do next; or looking at such a wide range of data that it’s difficult to know what to act on? Yeah, we know the feeling too.

If you find yourself stuck in an endless cycle of reporting and analyzing only to find yourself finishing in time to start the process over again for the next month (or quarter), we are here to help. Here are some do’s and don'ts when it comes to reporting and analytics in SAP SuccessFactors.

1) Do tell a story with your reporting & analytics data

Does your data look like a bunch of numbers or graphs on a page? Do you often question what’s being presented, it’s meaning and ask yourself why would anyone care? If the answer is yes, your data is likely not telling a story – or maybe it is, but not the story you want to tell.

Simply put, you need to create the narrative for your data to effectively tell a story. What message are you trying to send? What’s the context? What insights do you want your audience to understand? How do you want your audience to respond? Do you want them to act?

These are important parts of crafting your story. Data can show what is happening but not necessarily “why” it’s happening. The why in data is what compels us to respond. If you don’t create a story for your data, someone else will it and it may not be aligned with the story you’re trying to tell. Be sure that you have a good understanding of your data and when sharing with your team or leaders, ensure they can see the picture you are trying to paint (or eating the same slice of cake you served).

2) Do anticipate questions and know your audience

When presenting your data, it’s important to anticipate the kinds of questions that will arise. If you can’t answer those questions, it may diminish of the integrity of your data, and we know as soon as others start poking holes in it (or perceive there are holes or inaccuracies in the data) they are ready to move on, and you might not get another chance to tell that story again.

When it comes to your data, it should never raise a question you don’t already know the answer to. It’s your job as the storyteller to identify those things that may be a problem before your audience notices them.

Anticipating the questions and knowing your audience goes hand in hand. Are you presenting or sharing your data with executives? It’s likely they will have different questions and concerns than a frontline manager; present the story to each audience in a way that is digestible and meaningful for them, especially if you want them to act.

3) Don’t include metrics that are more labor intensive to collect than they have value

While this can’t always be avoided, a good general rule to abide by is if you are spending countless hours manually collecting data for a specific metric, it may be time to re-evaluate. We have heard from several clients (who shall remain nameless) that spend hours collecting data for their management teams, who never provide feedback.

From personal experience, we can share how frustrating it is to have to provide data for metrics that no one looks at and to add insult to injury, the collection process be completely manual. When selecting metrics, make sure they can be tracked and the process by which you are tracking is easily replicated. This is key for sustaining your analytics.

4) Don’t continue to add metrics and never retire old ones

Don’t keep adding more metrics to your list and never retiring old metrics. This can be exhaustive for the team who is responsible for meeting those goals. When you master a metric and can sustain meeting that goal, retire it from your regular report. You can always go back and check every now and then to make sure you are still on target; if not, add it back into the rotation.

Having a long list of can lead to “analysis paralysis” where you are so busy analyzing your data you don’t have time to digest it or do anything to affect it.

5) Do set achievable goals

You are tracking data for a purpose - more favorable outcomes. Otherwise, what’s the point? As you are setting goals to affect change in those metrics, make sure they are achievable. For example, let’s use a simple metric like days to fill. In recruiting, this is one of the main measures of productivity, right? The goal is to keep that number as low as possible, but you must understand what you are working with and set reasonable goals. If you are filling executive level positions, an unrealistic goal for days to fill those positions might be 30 days. Regardless of how hard that team works 30 days is likely impossible.

What happens when you set impossible goals? You deflate the team trying to meet them! Instead, set a more reasonable goal and once see that goal is consistently being met, then change goal and give the team something to strive for.

No matter where you are on your reporting and analytics journey, it’s important to keep these five main do’s and don’ts in mind. After all, the ultimate goal is to successfully report on your data, and take action where necessary. To do that you must know your data, and make sure your metrics are purposeful, actionable, and attainable (with some hard work). Adapt your reporting method for your audience and most importantly, tell a story. Your audience will be begging for another slice of cake, er, report.