{"id":1271,"date":"2018-10-24T07:03:10","date_gmt":"2018-10-24T07:03:10","guid":{"rendered":"http:\/\/grosum.com\/topTalk\/?p=1271"},"modified":"2018-10-24T07:03:10","modified_gmt":"2018-10-24T07:03:10","slug":"david-creelman-hr-analytics","status":"publish","type":"post","link":"https:\/\/grosum.com\/topTalk\/david-creelman-hr-analytics\/","title":{"rendered":"David Creelman, CEO, Creelman Research"},"content":{"rendered":"

\"HR<\/a>David Creelman is CEO of Creelman Research, based mainly in Toronto and partly in Kuala Lumpur. He\u2019s known for this research on people analytics, the future of work, and reporting on human capital to boards.<\/p>\n

He has presented his work around the world, including conferences in New York, London, Dubai, and Tokyo. Most notably he\u2019s spoken at the World Bank in Paris on the topic of reporting on human capital.<\/p>\n

David has an MBA and a BSc in Chemistry and Biochemistry. He\u2019s won the Walker Award from HRPS and been made a Fellow of the Centre for Evidence-based Management.<\/p>\n

\n

What leads to success in using HR Analytics to improve employee performance?<\/h1>\n

The single most important thing for HR Analytics is a deep understanding of the work. If a data scientist wants to understand the efficiency of warehouse workers, the first thing they should do is unplug their computer and take an Uber to the warehouse. They should spend a few days wandering around the warehouse watching what happens and talking to the workers, the supervisors, and the truckers. If possible, they should do some of the work themselves. Only then will they be able to understand the data, even if it\u2019s big data, that sits in their system.<\/p>\n

How can HR Analytics enhance employee performance?<\/h1>\n

The quick answer to how HR analytics can enhance performance is that it can help everywhere with everything. A more nuanced answer is that it can potentially help everywhere, so that means HR should take a broad look at all the drivers of employee performance and pick the areas where they suspect analytics will have the biggest impact.<\/p>\n

One tip for finding where analytics can have the biggest impact is to look for areas where there is wide variation in performance (John Boudreau and his collaborators have worked hard to bring this insight to HR). For example, if your best recruiters are only a little better than the average ones then it may well be difficult to find any way to improve performance. On the other hand, if your best recruiters are far better than the average (i.e. high variation) then that may signal a great opportunity where analytics can tease out why some are so much better and then find ways to make the average performers more like the great ones.<\/p>\n

What do CEOs look for in employee performance analytics?<\/h1>\n

CEOs tend to think of employee performance in terms of overall financial ratios. For example, they will be interested in revenue per employee and total salaries as a percent of operating costs. These metrics have some value in answering the question \u201cAre we, as an organization, getting fat (i.e. overstaffed)?\u201d<\/p>\n

CEOs are right to be concerned about this question because every manager feels they need more staff and that their existing team should be paid more. If the number of employees is going up and revenue is not (hence revenue per employee goes down) then that may signal a problem.<\/p>\n

CEOs recognize that there may be good reasons why any given financial ratio may move in the wrong direction, however, they want the metrics to draw their attention to possible problems.<\/p>\n

What is missing in terms of employee performance data that could make HR Analytics even more meaningful?<\/h1>\n

There is a very deep problem in that we do not know how to measure performance in many jobs. Often data analytics people will get ratings from performance appraisals<\/a> and simply turn a blind eye to how inaccurate these are likely to be.<\/p>\n

At some level measuring employee performance is simply one of the impossible problems that HR cannot solve and has to make the best of poor data. A more actionable position is that there are two cases where HR should work with the business to get better employee performance data:<\/p>\n