I\u2019ve always thought I was pretty good at analytics.Not being a practitioner who is sitting in the middle of data all the time, I get more time to just think about the type of analytics that it takes to really run the business.\u00a0 It\u2019s been a really long time since I discounted the usefulness of things like time to hire preferring things like quality of hire (efficiencies versus effectiveness measures).\u00a0 But I\u2019ve always fought with predictive analytics.\u00a0 In my opinion, they don\u2019t really exist in HR yet.\u00a0 We can trend our data and draw a trend line, but that does not predict our future \u2013 it simply tells us that directionally, something is going to happen if we don\u2019t change course.\u00a0 I\u2019ll admit that I walked into this session with a great deal of skepticism, I walked out with some great insights.<\/p>\n
The panel was made up of some great speakers.\u00a0 \u00a0Moderator: Jac Fitz-enz, Ph.D., (CEO, Human Capital Source), Laurie Bassi, Ph.D., (CEO, McBassi & Company), John R. Mattox II, Ph.D., (Director of Research, KnowledgeAdvisors), Eugene Burke, (Chief Science & Analytics Officer, SHL), Natalie Tarnopolsky, (SVP, Analytics and Insights, Wells Fargo Bank).<\/p>\n
Theme #1:\u00a0 Descriptive, Predictive, Prescriptive.<\/strong> Let\u2019s start with some definitions as the panel did, but I\u2019ll use a tennis example.\u00a0 I don\u2019t know if anyone has been watching the last few grand slams, but they have been using a good mix of all these types of analytics.\u00a0 Descriptive is simple.\u00a0 Roger Federer has one 16 tennis grand slams.\u00a0 (I\u2019m guessing as I\u2019m on a plane typing this).\u00a0 Predictive is next and basically tells us what our destiny is going to be.\u00a0 Roger\u2019s record against Nadal in grand slam finals has not been particularly good.\u00a0 If Rafa is on his game, hitting his ground strokes with the huge topspin he has, Roger is going to have to figure something out or lose again.\u00a0 Here is where the last few opens has been interesting.\u00a0 The broadcasters will sit there with the stats and say things like, \u201cIf Roger can get 67% of his first servers in, he has a 73% chance of winning\u201d or \u201cRoger needs to win 55% of Rafa\u2019s second serves to have a 59% chance of winning.\u201d\u00a0 Now we have prescriptive \u2013 the specifics of what to do in order to change our destiny.<\/p>\n Theme #2:\u00a0 Engagement.<\/strong> We probably focus in on this a bit too much.\u00a0 It\u2019s not because it\u2019s not important, but it\u2019s not specific or defined enough.\u00a0 I mean, we all have a definition in our heads, but for 99% of us, it\u2019s fluff.\u00a0 My definition of engagement is the intangible quality that makes an employee want to provide that extra hour of discretionary work when other non-work opportunities exist.\u00a0 Total fluff, right? \u00a0We can provide some correlations around engagement.\u00a0 If engagement increases by 1%, then turnover decreases X% and so on.\u00a0 What it provides is a great predictive measure, high level as it may be.\u00a0 We know we need to increase engagement, and it is indeed important.\u00a0 But it\u2019s not the key measurement we have all been lead to believe will solve all our problems.<\/p>\n Theme #3:\u00a0 Predict winning.<\/strong> OK, so if engagement is not the key metric, then what is?\u00a0 Well, I have no idea.\u00a0 I\u2019m not being snide, I\u2019m just saying that it will change for every single organization.\u00a0 If you are (mall) retail organization, then having really good salespeople might be what hits the bottom line.\u00a0 You could run the numbers and find out that if you rehire sales that worked for you the summer\/holiday season last year, those salespeople are 20% more productive, whereas engagement reduces turnover by 1.3%.\u00a0 Which metric are you going to focus on?\u00a0 Right, how do you get those experienced salespeople back?\u00a0 Instead of spending $1 on engagement, you could get 5 times the ROI on that same dollar elsewhere.\u00a0 What we want to do is not predict outcomes.\u00a0 We want to predict winning and understand what our highest contributors to winning will be.<\/p>\n Let\u2019s take another example, this one from the panel.\u00a0 \u00a0Let\u2019s say 5% of your workforce are high performers, but you can only give 3% of them promotions this year.\u00a0 You also know that the 2% of top performers who don\u2019t get promotions will likely leave the organization.\u00a0 Now you have a problem. \u00a0You can\u2019t afford to promote these people, but the cost of replacing top performers is extraordinary.\u00a0 Analysis like this quickly leads you to decisions which are actionable.\u00a0 At the end of the day, we need to compare our top drivers against our weaknesses to really figure out our greatest opportunities to invest in.<\/p>\n Theme #4:\u00a0 HR can\u2019t do it.<\/strong> This part sucks.\u00a0 Towards the end of the session, we walked through a statistical model.\u00a0 Yeah, we can end this post right here, but I\u2019ll continue.\u00a0 The rather brilliant by HR terms model was presented by Wells Fargo.\u00a0 Go figure an ex-finance person working at a bank would have this all put together.\u00a0 The point being, this was an ex-finance person, and the bak part is ot wholly irrelevant.\u00a0 All the stuff I said above really makes great sense.\u00a0 But when it comes down to executing it, HR in most organizations does not have the skillset to execute on it.\u00a0 We don\u2019t have very many statisticians in our HR staffs, and even if we did, HR executives would have a hard time seeing the vision and have the willingness to implement these technologies and models.\u00a0 All is not lost however.\u00a0 Finance has been doing this stuff forever.\u00a0 I mean, I\u2019ll bet you anything that if the interest rates drop by 1 basis point, Wells Fargo knows within seconds what the impact on profits are for savings, mortgages, etc.\u00a0 Can\u2019t we have\/borrow\/hire just a few of these guys?<\/p>\n <\/p>\n","protected":false},"excerpt":{"rendered":" I\u2019ve always thought I was pretty good at analytics.Not being a practitioner who is sitting in the middle of data all the time, I get more time to just think about the type of analytics that it takes to really…<\/p>\n","protected":false},"author":1,"featured_media":2310,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_coblocks_attr":"","_coblocks_dimensions":"","_coblocks_responsive_height":"","_coblocks_accordion_ie_support":"","footnotes":""},"categories":[388,27,19,8,2],"tags":[62,352,141,365,364,363],"class_list":["post-2108","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-all-posts","category-data-metrics","category-topics","category-strategies","category-hr-technology","tag-analytics","tag-hr-technology-conference","tag-measurement","tag-naomi-bloom","tag-prescriptive-analytics","tag-reporting"],"_links":{"self":[{"href":"https:\/\/systematichr.com\/index.php?rest_route=\/wp\/v2\/posts\/2108","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/systematichr.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/systematichr.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/systematichr.com\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/systematichr.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=2108"}],"version-history":[{"count":15,"href":"https:\/\/systematichr.com\/index.php?rest_route=\/wp\/v2\/posts\/2108\/revisions"}],"predecessor-version":[{"id":2110,"href":"https:\/\/systematichr.com\/index.php?rest_route=\/wp\/v2\/posts\/2108\/revisions\/2110"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/systematichr.com\/index.php?rest_route=\/wp\/v2\/media\/2310"}],"wp:attachment":[{"href":"https:\/\/systematichr.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=2108"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/systematichr.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=2108"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/systematichr.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=2108"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}