#2 ROI of Zegami HR
There are many reasons for HR organizations to pursue analytics. But the primary reason should be strategic insights: findings that can be gleaned from seeing the trends in workforce data, which in turn translate to better organizational decision-making, informed by better data. These insights create real value, and while that value is difficult to quantify, it is impossible to ignore. The right workforce insight could lead to higher engagement, better wellness, more equitable diversity and inclusion efforts, or lower attrition, in addition to many other benefits.
Where are there real dollars to be found in these insights? The economic arguments for better HR are relevant here. A few quick examples:
- Cost of recruitment vs. cost of simply retaining – The direct cost to fill a position can range from 25% to 100% (or more!) of that worker’s salary, a significant cost over simply retaining him or her. Also, beyond the direct costs, external hires tend to cost more (i.e., demand a higher salary) over simply filling the role internally (via promotion or lateral move).
- Turnover cost – Turnover cost manifests itself in more ways than recruiting costs. The lost productivity can amount to tens of thousands of dollars—per lost employee—per year. Avoiding this is key
- Higher-performance translates to productivity – Almost by definition, hiring more and keeping more high-performers makes your company itself more productive.
- Low engagement leads to lost productivity – It is well-documented how an “engagement gap” can quickly translate to a productivity gap.
And these are just a few from a far larger universe of potential forms of value creation that can come from intelligently working with workforce data. It is significant and tangible. Properly-executed analytics within HR leads to better workforce insights, which in turn leads to better-informed strategic decisions and better deployment of limited organizational resources. This is the true “value add” ROI of getting analytics right in your HR organization.
Case Study: Finding the Right Talent Through Strategic Insights
This case study sheds light on why strategic insights from HR are so critical for companies. In this case, a fashion and cosmetics retailer decided to look at data reflecting their trends in performance management, talent and hiring; this was for the purpose of finding out how to recruit and keep, the best employees possible.
The Challenge. This company started its analysis by looking at the distribution of performance data for its retail sales reps. They came to an expected conclusion. In fact, the data looked like most companies’ data probably does: a fairly standard bell curve distribution, with some high-performing, a lot of average/mid-performing, and a few low-performing employees. They wondered (as many organizations do): “Is there a way to move our organization so that a greater portion of our employees are high-performers?”
This is a very data-driven question and can serve as an example of how real value-creation can come from HR. But our case study organization was beset by data-related difficulties: What were the performance indicators that identify top talent? Where was the data on their recruiting process and candidates? Was turnover data relevant? Adding to the frustration, the data they needed to analyze was spread across several different systems, and they did not have one “unified look” that allowed for analyses across sources. To even begin addressing this question, they had to take stock of the different databases their information was stored in:
- Sales rep performance data was tracked in a salesforce-specific software program;
- Employee performance ratings were maintained in their HR software system, where annual performance reviews were logged;
- Candidate applications and interview records were in a Recruitment-specific software module;
- Skill sets were part of employee profiles, maintained on the company’s intranet, which was managed by IT, not HR.
How Zegami HR Could Help. Finding relevant insights here relied on consolidating the various different data elements into a single view, a “single point of truth”. To analyze and find trends, they might use an Analytics program like Zegami HR. Taking advantage of APIs, they could feed all of their disparate databases into the Zegami analytics platform, and view trends across many different sources of information.
Action: So what could they do, now that previously siloed data were now accessible and comparable? They planned several steps:
Step 1. Compare salesforce performance data vs. annual performance review data (i.e., performance ratings), to see if identified high-performing employees were really the most financially-productive employees.
Step 2. Analyze the universe of employee profiles, and categorize identifiable employee traits (e.g., self-reported skills listed, education/college attended, highest attained degree, major/specialization, years of professional experience, years with the company, prior industry experience, or experience working for a competitor).
Step 3. Explore the employee performance data in Step 1, and compare it against the “employee traits” data in Step 2 in a massive correlations exercise, to identify traits that correlated to high or low performance later on in one’s career.
Step 4. Take stock of the traits that are correlated with high performance (say, college education and prior experience with a competitor in the industry); then, mine the profiles in the current job applicant/interview candidate pool, looking at a data dump from CVs and LinkedIn profiles. This way, they could see which candidates had the characteristics that were most correlated to current high-performers.
Insights: With the right data and real insights, they could start a chain reaction of strategic value-add:
Through strategic insights that started with HR by identifying high-performers, and ended with HR by augmenting recruitment practices, this company could begin to build an entire workforce of high-performers and reap the benefits thereof.
In the case of this company, the key to providing value-add through HR was the integration of many different databases, into a single point of truth, and then conduct that analysis quickly. Technology today allows HR departments to do this proactively, thanks to the ability to sync programs and data sources together, provided you have the right Analytics toolkit to help.
Tools like Zegami HR allow companies to aggregate and synthesize that information in a meaningful way. At last, analysis across many different types of data is a real possibility for HR.
Other Similar Analyses
An entire book could be written on the long list of potential insights driven by analytics, and the value-add that can be created by the organization that gets HR analytics “right”. Here are a number of examples:
- Recruitment: Candidate screening (i.e., the case study above) – Find the right people by running correlation analyses with the characteristics of past high performers; see what traits in a candidate are indicative of them being a high-value employee if hired.
- Recruitment: Narrow the skill gap – Data mine candidate traits in recruitment databases (such as CVs or LinkedIn), to more precisely narrow-in on the candidate profiles with the skills you need.
- Attrition trends: Retain the best people – Go beyond simple reporting of attrition numbers and employee leaver profiles. Find the predictors that lead to unwanted leavers, and strategically pre-empt it.
- Employee engagement – By combining employee engagement survey data with other fundamental employee indicators from HRIS, you can both identify engagement drivers and localize problematic areas.
- Pay fairness – Explore the drivers behind your gender pay gap, which may rely on more unclear, harder-to-access data than you might think (e.g., team makeup, manager info, performance review bias, and more); closing this gap within your company will lead to a more equitable, better-engaged workforce that will, in turn, lead to higher productivity and better retention.
- Diversity and inclusion – Extend the analysis of all workforce fairness issues beyond the gender pay gap, to build a more inclusive company; find the specific fairness initiatives that drive higher engagement levels in the data, and direct your investments accordingly.
- Compensation benchmarking – Spend your limited rewards dollars in a targeted way, by identifying the below-market individuals who may require an increase or above-market individuals who may not justify further spend; do all this at the push of a button, seamlessly and intuitively, without the need for lengthy report-outs or data dumps.
- Rewards optimization – Survey and explore workforce preference data on what forms of rewards are perceived as most valuable to different subsets of employees (e.g., salary vs. bonus vs. equity vs. healthcare or retirement benefits), allowing you to prioritize spend most effectively.
- Employee/organization development – Find the skill gaps within your organization, and spot trends in training efforts that most effectively “skill-up” your employees and close this gap.
Summary: How strategic insights can generate ROI with the right tools:
- Value-creating strategic insights is the main reason companies employ analytics of any kind.
- These insights lead to better intelligence on your organisation and allow you to make better decisions, which can generate ROI in a myriad of ways.
- In HR, this value comes from knowing and understanding your workforce better, and thus, improving your company’s most important asset—people.