HR Data Alone Won’t Make You Strategic


Embedded analytics — defined by Gartner as analytic capabilities that are “easily accessible from inside the application, without forcing users to switch between systems” — are one tactic that has been heralded as an effective approach for facilitating data-driven decisions.
For HR leaders, the promise of embedded analytics is especially appealing, due to several apparent benefits:
Given the prospect of free, in-context analytics that are immediately available, it’s not hard to understand their allure for HR. Unfortunately, as with many promises that are appealing on the surface, there’s a catch — and it’s a big one: HR leaders quickly find out that the answers to the strategic business questions they have don’t live in their transactional HR systems.
If the embedded analytics only include data from their HR system, the benefit they provide is very limited.
To be truly strategic to the business, HR needs to be able to connect the workforce to business results that are top of mind for the CEO. For instance, it’s not enough to know what the retention rate is; what matters to the CEO is how retention impacts profits. It’s not enough to measure employee engagement; what matters is knowing how this affects customer satisfaction.
The answers to the strategic questions business leaders have live in a vast array of disparate systems:
And that’s all before business information — sales, financial, customer, and other business data critical to understanding how people programs contribute to business results — is added to the mix.
What’s clear, then, is that embedded analytics, which cover only a single system, are not enough.
This realization has prompted some organizations to pursue a ‘build your own” business intelligence (BI) project. And these projects are anything but free.
The additional work required to get true value from embedded analytics may be an unwelcome shock for buyers, but to HR system vendors, it’s no surprise. In fact, the extra costs are often a key part of their business model.
If your team is pursuing analytics to provide more strategic value, then you need to be aware of these hidden costs:
Data integration: Because the data required to answer critical business questions about the workforce lives in multiple systems, it first needs to be collected and standardized, generating the need for a data integration or data warehousing project that can easily come with a seven-figure price tag.
Some HR system vendors will require external consultants and third-party applications to manage the whole process properly, which can add to both the length and cost of the project.
Historical data: HR system vendors often do not include historical workforce data in a new implementation, severely limiting your ability to perform predictive analytics.
To work around that limitation, you can either wait 18 to 24 months to build up a data set that’s big enough for accurate predictions or pay for the cost of adding historical data — a project that can run in the six figures for just one year of data.
Future changes: Even after you’ve completed the initial data integration project, you’ll still be on the hook for any changes in the future. Every time you need to add a new field, metric or data source to the analytics, or if your organization structure changes, you’ll need to pay to have these updates made.
Before you commit your team to making do with “free” analytics, take a look around for a workforce intelligence solution that will deliver where embedded analytics fails.
Look for a solution that integrates all your workforce data sources — no data warehouse needed — and gives you the ability to easily dive into historical data so you can make important predictions about your workforce.
Another perk to look for is a vendor that takes care of any data onboarding and management you need for the length of your contract. This means that when future changes are made, you won’t have to pay to have these done, which ensures you are always making decisions on accurate, up-to-date information.
This article originally appeared on the Visier blog.