This year I think I have meet with more companies, thought-leaders and partners on the topic of Analytics than in any of my previous 16 years of experience in this field. Why? Company executives are demanding from Human Resources, information about their workforce that is directly connected to improving the business. This is great and has been a long time in the making.
The challenge is that today’s HR thinking and Analytical tools are designed to help HR improve HR, not to help HR improve the business. Because of this, HR has and will continue to face significant challenges in gaining executive sponsorship to meet this demand and unfortunately market and survey data support this conclusion:
2010 IDC Market Size Report - Where your executives are spending their money:
- $18B+ spent on all business functions except HR
- $178M spent on HCM Analytics i.e. less than 1% of the total BI spend in 2010 was for HR
2010 CedarCrestone HR Technology Survey-Workforce Analytics:
- 88% of survey respondents have a simple management reporting (e.g. excel)
- 58% of survey respondents have a HR operational reporting
- 46% of survey respondents have HR Dashboards
- 11% of survey respondents have a dedicated analytics platforms (e.g. a warehouse)
Recent Poll of 175 people attending an iHRIM conference:
- 63% of poll respondents have basic compliance reports and use spreadsheets
- 21% of poll respondents have HR dashboards
- 9% of poll respondents have analytics for workers outside of human resources
- 6% of poll respondents have a look at non-human resource data
- 1% of poll respondents use Predictive Analytics
These numbers are telling so what can Human Resource do to deliver on this demand?
- If you have them, start over with your manager facing dashboard(s): Chances are that you probably deliver a single HCM Dashboard for all of your managers and that’s not enough information. Think about it this way - would you force payroll, compensation, benefits, recruiting etc to use a single dashboard that gives all those teams that exact same information, like headcount and performance rating distributions? No. Every HR Function, just like every business function, is distinct from the other and generic HR dashboards don’t deliver what people need. These dashboards need to be role based and specific to the function that a manager/executive is in. Manufacturing, finance, customer service etc should all have their own HR dashboards which reflect the unique needs of their groups.
- You want your managers and executives to see and use the information in these dashboards so give them reasons to: Make these dashboards sticky, make them actionable, make it the primary portal for all of their HR Actions and push updates to them.
- Notice I keep on saying executive AND manager HCM Dashboards. An executive leading a multi-level organization with 5,000 people in it is going to need different types of information than a 1st level manger leading a 12 person team. So have HCM Dashboards to reflect these differences in a Manager HCM Dashboard and an Executive HCM Dashboard.
- Do formal and informal focus groups with each business function: Trust me, your managers and executives want to give you their opinion on what information they need to run their business. Go meet with them, document their requirements and then deliver on the ones that make sense.
- Create an ongoing internal advisory that has a mix of managers/executives from across all different business functions: This is a good place to obtain agreement on common dashboard requirements from across the company and yes, while every business function is unique, they will have some common requirements (e.g. cost of an employee).
The reality is that if company executives do not get effective and pertinent HCM Dashboards, they will find a way to get it without Human Resources.
The "Economic Recession" officially ended back in 2009 however, companies' continued to shrink their workforce either through layoffs, attrition and/or 'managing out' their bottom performers. While wrapping up March's WARP (monthly workforce measurements of companies within the Fortune 500) report I also realized that there are some truly great indicators that leads me to the conclusion that the "Workforce Recession" we have been in, is nearing an end too.
- 0% Growth in the Workforce: Having gone from continuous Quarter over Quarter negative growth in the last 4 years, a 0% growth is looking pretty amazing.
- 95% of the companies are profitable: A 7% increase from the previous quarter and a 30% increase from the quarter before that.
- 75% of the companies opened more positions in February than they did in January. This number has been increasing steadily since November of last year.
- 21% increase in opened positions for February as compared to January: Big increases (500+ new positions) came from IBM, GE, KBR, and JPMorgan.
- Only 0.01% of the companies had a layoff and in those cases, the percentage of workers laid off was 0.001% of the total workforce.
- Google and Apple alone are hiring 93 recruiters globally.
It may be a bit premature to say we are completely out of the "Workforce Recession" but keep your fingers crossed
Every dashboard and analytic I have ever delivered has been 100% accurate in every way shape and form. If you believe that, then you’d also believe that I can bike as fast as Lance Armstrong. All jokes aside, I would like to be able to deliver a 100% accurate dashboard but I accepted early on that this is nearly impossible and that this is not a problem just in HCM but across all areas. Just to clarify, I am not talking about the simple analytics such as ‘performance rating distributions’ or ‘jobs currently not in use’ which can be put in an excel spreadsheet. Those can and should always be accurate. I’m talking instead about complex analytics such as ‘headcount trending’ or ‘workforce profitability’ which require trending, complex calculations, roll ups by multiple hierarchies, etc. Generally, complex analytics are hard to do and simple to get wrong.
In your first iteration of a headcount report, it is unlikely you will be able to deliver the full picture. The mainstays of a 1st iteration of a headcount report are; headcount by supervisory and/or department hierarchy, types of movement in the organization (e.g. hire, fire, transfer, loa), employee vs. contingent, and maybe some trending. This is not by any means a complete picture and to get that, you’ll need to add things like all worker types (e.g. vendors, partners, etc), matrixed organizations, headcount by project, etc. These are things that you may never be able to deliver on.
Just to make you feel a bit better, you will also with 100% certainty, have data integrity issues and most likely a calculation error or two. Getting manager to manager transfers within the same department to roll up the organizational hierarchy correctly to the VP who wants to see Internal Mobility is a surprisingly tricky thing to get right.
With this in mind you will need to head off the inevitable calls telling you that your dashboards are inaccurate and thus unusable. Although it may seem counterproductive, you should tell your consumers that there will be errors but you’re working on corrections and you can do this by/ through:
- a formal statement someplace in your dashboards which informs your consumers on how to report an error
- a link to a document that has all the definitions, calculations and data sources for all of your analytics within the dashboards
- While pretty graphs are great for instantly communicating lots of aggregated and calculated information; for determining root cause analysis however and for ultimately taking corrective action, the consumer needs to look at underlying information (e.g. a simple turnover graph that can drill into a table separating turnover by locality, job, performance ratings etc).
- associating accuracy and usage information to each of your analytics; similar to the score you’d see when deciding what latest mobile app to download for example. This way you can focus your efforts on either correcting an issue, various improvements or discontinuing now irrelevant dashboards and analytics
- placing your release or revision date someplace prominently on your dashboards and linking it to your release schedules
Complex analytics and dashboards are hard and I wish you luck with them - knowing and admitting publically that there will be problems with these, will go a long way in giving you credibility and leeway in getting them corrected.
In a recent survey, over 25,000 (as of January, 2011) workers ranked how they felt about their CEO on a 1 to 10 scale. A ranking of a 10 signified that workers felt the CEO was an effective leader and a ranking of 1 meant that they thought he/ she was highly ineffective. While this might be an interesting metric, it is not a compelling metric and alone, does not show how the workers’ view of the CEO impacts the profitability of a company.
Now, a compelling metric would be to take these survey results and compare them against “Profit per Employee”. I did that and it generated some very surprising results (see chart below). In 67% of the industries, a worker's negative view of the CEO had no negative impact on Profit per Employee. In fact the industry that had the lowest “Profit per Employee” had an average CEO score 3 times higher than the industry that had the highest “Profit per Employee”.
Don’t share this with your Senior Management, it may start a horrific new trend
How to Interpret the Heat Map:
1) The size of the industry box (e.g. Financial Data Services) is determined by the value of their Profit per Employee. So Financial Data Services has the largest Profit per Employee ($13,578) and Construction/Engineering has the smallest ($20).
2) The color indicates the CEO score. The darker the blue means workers view the CEO as effective. The more grey means workers view the CEO as ineffective.
3) More information on heat maps.
4) If you haven't updated your browser's flash add-on in a while and can't see the heat map, click on the "Full Screen" link at the bottom left.