The ethereal concept of “big data” is coming down to earth to help organizations address key business challenges and make better decisions. That’s the vision of Vestrics, a 12-year-old consulting firm that has transformed itself into a software company offering a software-as-a-service (SaaS) platform for helping companies make better decisions related to their human capital.
According to Brian J. Kelly, President and CEO, the big opportunity is to go beyond “simply slicing and dicing numbers and calling it analytics. That’s analysis, which is an important first step, but we believe that’s doing a disservice to true analytics.” Kelly says that analytics, and the Vestrics Vision platform, are about establishing clear linkages and correlations between variables, then moving to establish causality – i.e., one thing causes another to occur. Providing causal linkages in a way that’s repeatable and scalable, so that companies can make better decisions about investments in training, incentives, or practically any initiative involving people in a way that was never before possible. In the recognition field, the service is offered by Engage2Excel, which recently changed its name from Tharpe Robbins to reflect its focus on engagement. Companies such as a division of Xerox also use the platform as part of a service it offers to clients, and Kelly says Vestrics is quite interested in providing support to all types of solution providers bringing engagement applications to their clients.
By offering a cloud-based service and providing insight almost as quickly as data is gathered, Kelly says Vestrics enables management to test hypotheses on an ongoing basis, such as: Will adding such-and-such training elements help us retain employees? Will an investment in corporate social responsibility produce the desired results? What employee characteristics in call centers produce the best call outcomes? Will changing the incentive plan have the desired result?
The key to success, he explains, is to have a clear hypothesis related to a human capital initiative, a sufficient amount of relevant data going back in time, and an ongoing means of capturing and plugging that information into a technology platform that can identify key correlations, use regression modeling to establish causality, and “what-if” analyses to map and predict potential future outcomes.
Kelly is excited about the potential for analytics and says he has seen considerable change since he entered the field about 15 years ago. “I still think we’re about in the bottom of the second inning with a lot of room to run,” he notes. The biggest companies, he says, are already creating departments specifically focused on analytics; many others need help developing and designing a repeatable and scalable platform for analyzing available data to make better decisions. He believes his company can serve both.
What has changed in the field, says Kelly, is cloud-based technology with advanced applications that can automate the process of establishing causality in relationships between variables, which allows organizations to not only understand what happened in the past, but map the most likely outcomes of key human capital decisions in the future. He believes his company has opportunities both to help large companies with in-house analytics management crunch data more efficiently, as well as companies without in-house analytics departments that need help setting up a platform and a means of profiting from it. That potentially includes management consulting firms, incentive, loyalty, and human resources firms that wish to bring more analytics-based solutions to clients.
“What we’re talking about is using data to make better decisions,” he says. “How do we balance both the qualitative and quantitative when making important decisions?” Kelly explains there are three distinct areas to address.
- Descriptive analytics is what is happening in a workforce; allowing the company to segment data; see trend lines such as how much do we pay and where do people turn over; data aggregation and reporting; a report on what is happening.
- The next element is what could happen. This is where a company isolates impact and determines the ROI of a decision. It’s about establishing causality and relationship modeling. The idea is to isolate variables associated with specific behaviors and outcomes. This enables the company to look at what could happen.
- The final element is prescriptive – tell me what should I do? What is the decision I should follow and what is the most likely outcome? This is about looking at “what-if” scenarios so companies can understand a decision on a risk-adjusted basis.
“What’s challenging for everyone is to get to prescriptive,” Kelly says. “You have to do the math, the statistics, and it’s often hard to build and scale. And so many vendors often default to descriptive analysis and trend lines and then call that analytics.”
True analytics, he explains, is about modeling data that can be used to prescribe and predict outcomes that may bust myths. “People might think a training program would drive engagement. They get some anecdotal information but can’t get to a causal relationship. They aren’t effectively managing that spend until they really know the results.” Some people in corporate America don’t want to run the risk of knowing, but in fact that data often does show a causal relationship between initiatives such as training and lower incidents of accidents and higher levels of retention.
The Vestrics model, says Kelly, boils down to helping clients make better business decisions. “This is part of what makes us successful. We embed advisory services into our subscription model. We walk clients through the entire process and teach them how to fish. And, over time, clients use us less and less for advisory services because they can do it on their own.”
What can analytics do and not do in human capital? “Software platforms generally cannot make the decision for you,” says Kelly. “That’s where people make a mistake. They see a quantitative result and forget the qualitative aspects of people management. At the end of the day, quantitative models can’t account for every variable, but can establish probability of likely outcomes. The idea of managing and minimizing risk should be at the forefront of your discovery. Software can do an awful lot, but you need a business leader to make a decision using data to calibrate the decision. Were we right? Have variables changed? Has the climate changed? Are there other changes? Is this is a blip? Is this the right thing to do on a long-term basis? Those are the types of decisions a leader has to make.”
For more information on Vestrics, contact:
Joe Grohovsky, Sales Director