Last week I had the honor of being invited to speak at the Melbourne HR Talent Community with Steve Pell of Intrascope Analytics. Steve and I discussed analytics for HR, why "Big Data" is all the rage, and why most of the valuable data about your workforce is already sitting inside your internal systems (Big Data or Small Data, it's all about the insights). The below video is 8 minutes extracted from the 45+ minute conversation.
Steve is the Founder and CEO of Introscope Analytics. Intrascope's mission is to help business and HR leaders connect the dots between people strategy and business results, by delivering powerful insights about workforce behaviour in real time.
The Melbourne HR Talent Community isn't your usual networking group. It now has over 600 members, and 70+ members meet monthly to discuss a broad range of current HR issues. If you think networking is a 4-letter word, you can't count but you can enjoy their monthly meetings and the conversations in the LinkedIn group.
Transcript (provided by Rev.com):
Alex Hagan: Big Data is used very extensively in the consumer space to take all of these different interactions that consumers have with brands, and find patterns in that data to essentially, to put it cynically, sell better to those people. So, the type of data that people are crunching in the consumer space are things like Visa that apparently can predict whether you’re about to get divorced based on your spending patterns of those of your spouse.
Steve Pell: But, I think just to jump in there that kind of takes it to a scary level that can be intimidating for a lot of people to think about …Or you read the case about Target where they were talking about predicting pregnancy, but do you want to go back to the way that we kind of talked about it in terms of, the best way to think about what everyone’s talking about, when they talk about big data, is really just understanding patterns. Instead of thinking about this as being a huge scope of plugging together everything in your digital life, it’s really just looking at data whether it be big or small, and finding patterns about people.
Alex Hagan: And that’s the thing about big data as well, it’s increasing the consciousness that using data to support your decision-making, leads to better decisions. So, whether you’re analyzing segments from Twitter feeds or whether you’re analyzing Visa transactions, and all this very complicated stuff that people are doing, the value for HR is realizing that there is a lot of data we already have within our systems; within our organization, that can give you insights and we’re not getting today.
Steve Pell: The first take-away is size doesn’t matter in this game. Big or small it’s about finding the patterns in the data. Whenever anyone says big data, they’re usually it as a term for basically finding patterns in data, but it doesn’t really matter about scale here. Don’t get caught in the technicalities. Do you want to jump into; I think the ‘Moneyball’ analogy is a really good one.
Alex Hagan: Has anyone seen the film Moneyball?
Speaker 3: I’ve seen it yes.
Alex Hagan: So whenever someone talks about data particularly for HR, it’s kind of a gimme - someone wrote a book, and then made a film about analytics and using data to support HR decision-making. So you can’t hear about analytics for HR without hearing about the ‘Moneyball’ analogy because it’s a great one.
Moneyball essentially was about the Oakland A’s in their 2002 season, reinventing what success looked like for that organization, and then hiring to that profile of what meant success. The common wisdom was that if you want to put together a team of superstars, they could all hit home runs, they look really good on the field, they were good for the marketing dollars, but when they analyzed the data, what they actually found was, those things didn’t matter so much, as just getting on to the next base - however you did it. You could walk, you didn’t have to hit a home run. The measures of success; what actually drove how many games that you won, was much simpler than that. A hundred plus years of the way they’ve been recruiting these people was wrong essentially - or at least efficient. What they did was realigned all of their talent acquisition strategies, which is essentially what they were, and they found they could get three players and pay them a quarter of a million dollars a year each, still a pretty good salary I would suggest, but that would get them the same result as one superstar player that they would pay seven million dollars a year. In that way, they were able to compete. They had a payroll budget of thirty two million, I think it was, and they were able to compete effectively with teams like the Yankees who had a hundred million dollar payroll. So, three times their payroll. They did it essentially through data.
Steve Pell: I think frankly for me, one thing that’s really meaningful about using Moneyball as an example, is that to use the HR analogy, none of the day-to-day stuff really changes. You’re still stepping up to the plate. You’re still hitting, you’re still pitching you’re still throwing, in the same way that the day-to-day practice of what happens, from a transactional HR perspective, doesn’t really change. Where this changes the game is at the strategic level. When you’re planning for the future of the business, and when you’re dealing with the C-Level. That’s where this fundamentally changes the game. But in the day-to-day level, not so much, you’re still doing the standard practices that people know and recognize as HR. That’s kind of I think, an important distinction to make.
Alex Hagan: I think what you get is the ability to find out where those practices are actually delivering value for your organization as well. So, to give you an example, does anyone here use psych assessments in recruiting within their organizations? Okay. So, psych assessments are used to predict who’s going to be a top performer once they become an employee and get into your organization. But how many people have actually connected that predictive value to results once …one person, (laughing) a psychologist studying for your PhD so, that’s the one person who’s done this. (Laughing) So, we’ve got all of this data available to us. We have the results of the psych assessment, and then in the long-term we know how well these people perform, how long they stay with the organization, or whatever it is that’s your measure of a successful candidate. But actually connecting those two can give you a great deal of value.
Steve Pell: There will be so much more valuable data sitting within the organization than outside the bounds of the organization that focusing efforts there because it’s so much deeper in terms of you have these longitudinal, the history of data where someone’s contributing inside of an organization between a couple of hundred, and a couple of thousand pieces of data a day potentially. If you go external and look for these data points you might get one or two. One of the really interesting things we can do is say, this is success. We’re not going to tell you what success looks like. You give us your talent ratings. What is it in the way that people are behaving that is leading to that outcome? What are the patterns that are happening at three, six, twelve months prior leading up to that review, that are different across your review levels? In some of the cases that can be as simple as having … I commonly see major difference in senior sponsorship, so you look across the people you’re giving really high performance reviews to, and people you’re giving really low performance reviews to, and there’s just a really big gap in how many people at senior level in the organization those people have access to. It’s common sense but when you quantify that, and say that there’s this 60% gap between these people, you can go out to the workforce and start talking about practical things that you can do to really push yourself potentially up those performance categories by doing the links.
