HR Data Danger: The Risks of Inaccurate Business Data
Businesses leverage customer data to deliver a better customer experience and are learning that to do that effectively they need an attribution model. That is measuring customer activity across every channel both on and offline so they can truly understand the influences behind their buying decisions and view the full customer journey. Pretty smart right? So, why is it that internally businesses continue to make assumptions based on inaccurate people data and incomplete employee journeys, leaving HR to pick up the pieces and attempt to create a ‘best guess’ picture.
In the latest issue of Collaboration Magazine HR Technology Specialist at Access
Group Damian Oldham discusses the risks of a false data bubble. Today we explore the key issues raised in that article, offering further insight on the challenges and risks of running a business existing in a false data bubble.
Masking unidentified risks that block progress
Article excerpt: By failing to align say, financial performance with employee engagement and absenteeism, companies create a ‘false data bubble’ that masks unidentified risks.
Just like the customer journey, without a full view of the employee journey and connected data you could be making decisions that have a negative impact on other areas. For example productivity statistics in one team could seem high but if the engagement is low there is an unidentified flight risk. Here increased productivity may have initially felt like a cause to celebrate, yet when the data is joined up it reveals that employee satisfaction has suffered as a consequence - not so good.
According to a practical guide on HR analytics Deloitte describe four levels of data analysis maturity for HR. 56% of organisations function at Level 1, which represents a high-risk ‘false data bubble’. A level they describe as:
- Using data to understand and reflect on what happened in the past - and maybe going further to draw conclusions as to why past events played out in the ways they did. The fundamentals of this level of HR analytics are understanding already available data and eventually coming to an agreement as to what the data means for the company.
It’s a similar data dilemma to making key marketing decisions without a view of the full customer journey, even if your PPC ads are seemingly not performing well, customers may be seeing those ads and then visiting the store later that week. Employees are your customers and people data is your route to understanding them - if it’s accurate.
Senior managers too busy looking backwards
Article excerpt: As a result [of a false data bubble], senior managers spend too much time looking backwards, perhaps wondering what more they could have done to retain a valued employee, rather than putting a long-term plan in place to reduce the chances of it happening again.
In a Harvard Business Review article “the Data Doc” and President of Data Quality Solutions Thomas C. Redman points out that:
“The reason bad data costs so much is that decision makers, managers, knowledge workers, data scientists, and others must accommodate it in their everyday work. And doing so is both time-consuming and expensive. The data they need has plenty of errors, and in the face of a critical deadline, many individuals simply make corrections themselves to complete the task at hand. They don’t think to reach out to the data creator, explain their requirements, and help eliminate root causes.”
Chances are, senior managers throughout the business are under pressure to find meaningful data insights but tackling disparate data points that don’t make sense. Instead of focusing on forward planning and having access to data that helps them drive commercial results for the business, they are wasting time looking backwards and grappling with several reporting funnels. Not only does this not drive profit, it also causes additional stress for managers that can then impact employee retention.
Time wasted trying to find meaningful insights
Article excerpt: Our research shows that HR teams are all-too-aware of the dangers of relying on incomplete or conflicting data to make decisions. Over a third of our survey respondents see inefficiencies, excess administration and poor collaboration as their biggest hurdles for the coming year.
This should come as little surprise to those who face a constant battle, chasing different departments for information and manually updating various systems, or worse still, spreadsheets. In a Forbes article on HR Data Big Data expert Bernard Marr captured the issue well when he wrote:
“Despite having access to a wealth of data, in my experience, too many HR teams spend the majority of their time on admin tasks or legal issues. Clunky staff appraisals, the day-to-day minutia of recruitment and people management, and wasteful, expensive activities like annual staff satisfaction surveys take up time that could be better spent elsewhere. Plus, there’s the issue that HR is traditionally seen as very people-oriented, and not so much about numbers and data.”
Even if you do manage to collect enough data to tell a positive story that you can share at the next board meeting, the chances are it won’t marry up to wider business stats and yet again your findings will be brought into question. A frustrating cycle of wasted time working with data that doesn’t tell a full story, no matter how many ways you manipulate it.
Siloed data is blocking profitable growth
Article excerpt:
When you have multiple – and sometimes conflicting – streams of data, there is no single version of the truth across the company. Reports generated from disparate software packages and spreadsheets quickly become outdated, and do not provide a firm basis for strategic decision-making.
A Forbes Insights and KPMG report found that 84% of CEOs are concerned about the quality of the data they’re basing their decisions on, Gartner also measured the average financial impact of poor data on businesses at $9.7 million per year. Costs, impacted by a combination of loss in reputation, missed opportunities and higher-risk decision making all come with low data confidence.
It’s easy to get caught up in data that seemingly tells a positive story for your department, the problem is these ‘success stories’ don’t all line up with each department head presents their findings to the board. This creates more conflict and question on the credibility of the data and blocks profitability and progress as a consequence.
Ultimately, disconnected data impacts cash flow and margins alongside further financial loss with license fees, maintenance and support for multiple applications.
The impact of a disconnected workforce
The digital landscape is saturated with millions of tools that can make employees’ jobs easier in isolation. Easy access tools that are free to use and a quick fix for their own departments needs. The problem is that there is little way to connect those tools across the business and employees are then so married to their own way of doing things remembering passwords and accessing separate portals becomes overwhelming. This means that each department is communicating and measuring their performance in a vacuum. Even if the HR systems are in place to help employees track their development and stay connected employees just aren’t using them anymore.
According to our research, just 4% of HR professionals have complete faith in the accuracy of their people data to make decisions, while another third have limited confidence. Making key business decisions based on a false data bubble is high-risk and despite the temptation to continue existing in that bubble, it really is time to invest in a connected data strategy for the business.
For more HR insights you can read the latest issue of Collaboration Magazine or find out more about the issue of HR data confidence in our latest blog ‘How connectivity can help resolve HR data confidence’.
