The Problem with Analytics in HR and How to Fix It

Let’s be honest: analytics is a beast to tackle. Using analytics is not as easy as plugging in data and waiting for the cool tool to create pretty charts with insights. If that were the case, we would all be fluent in analytics. But using analytics, and using it effectively, takes analysis, planning, and time and investment from both leadership and the team. How many organizations, especially smaller ones, can say they have all of that?

In the last few months, I’ve been leading the reporting effort at Argosight for one of our clients. Working with HR data on a weekly basis allowed me to see potential trends and insights that could improve the client’s HR operations as well as our own recruiting processes. Last month, we added a layer of analytics to our reporting. The analytics is driven by a proprietary tool we are developing with a partner. The analytics gives us insight into recruiting metrics, candidate pipeline movements, as well as historical trends in hiring. The tool pulls data from our ATS and updates it approximately every hour so our analysis is almost in real time. I must say, the ability to use analytics to understand what’s going on and make decisions and changes to current practices has been extremely valuable.

However, my ability to do valuable analysis is rendered useless by the fact that the data is incorrect. I’ve spent more time in the last few weeks trying to understand our data model and make appropriate changes to the data and the algorithm than actually using the tool. It’s a frustrating process because I strongly believe in analytics, and I desperately want the recruiters as well as the management team to start using it. But, as much as I would like the team to use the cool charts and glean insights from them (like I do), I can’t expect the team to use the tool if the data behind the charts are incorrect. I, myself, don’t trust the insights. Is this experience normal in the industry?

In Argosight’s most recent snap survey, we asked members of our HTRM LinkedIn community about their own experiences with analytics. We wanted to know:

·       Are they using analytics? If not, why?

·       What was the motivator behind using analytics?

·       What level of impact has analytics had on their organization?

Surprisingly, the reasons why people are not using analytics and why analytics has not been too impactful on organizations are the same:

1.      Poor data quality

2.     Lack of skills/ competency in data and data platform

3.     No investment from management

For the approximately 50 HR executives we surveyed who actively use analytics, the impact of analytics on their organization has been average (5.1 points on a 10-point scale). Based on these results, one could say that using analytics makes no difference. In fact, it’s probably better NOT to use analytics because you can save on the time and money investment.

But, I would argue that a better way to look at this is to address the three issues pointed out above. If these HR executives are getting average impact with poor data quality and little to no investment from the leadership team, imagine the impact analytics can bring to your organization if you’ve done the proper analysis and planning in advance.

In the last couple of weeks, I’ve spoken to and/or listened to various business leaders on their experiences with analytics. From these conversations, I’ve distilled three recommendations for how to use analytics effectively and how to take analytics to the next level. These recommendations include:

Know what you want to measure

This may seem obvious, but many people start using analytics without knowing what they want to measure. Since there is so much data available, there is the urge to use all the data and see what it says. This method usually leads to spending a lot of time figuring out if the data points are useful. The amount of data, in this instance, distracts rather than focuses the process. If you know what you want to measure, you narrow the data you use and give meaning to the project. Having a purpose to analyze the data will motivate the team and keep the project within scope.

Tie analytics and what you want to measure to the business strategy

To get buy in from the leadership team, the results of using analytics should benefit the business in a defined way. If management cannot see the link between analytics and a positive impact of analytics on the business strategy, they are less likely to put their support behind it. Having support from leadership will give importance to the project as well as the time and resources needed to drive the project to success.

Pick the right tool and platform for your skills/ needs

Depending on what you are looking to do with analytics, the tool you need can be simple, like data visualization tools, or robust, like tools with predictive models. Understanding your needs will allow you to closely assess the capability of the tool so that you don’t overspend on capabilities you don’t use. Additionally, it’s important to assess the skills on your team and match them to the platform of choice; lack of analytics skills can lead to a deep learning curve which will delay or derail the project.

The market for analytics software is changing quickly and advanced analytics capabilities are more readily available now than ever. Although it may be enticing to try the latest and greatest tool, the point of using analytics is to gain insights to improve business. Organizations should knowingly and purposefully approach analytics like they would in replacing big enterprise systems. If the business case for analytics is there and if diligence has been done, applying analytics to HR data can create a competitive advantage not only for HR but for the entire organization.