By: Greta Roberts, Conference Chair, Predictive Analytics World for Workforce 2016
In anticipation of his upcoming Predictive Analytics World for Workforce conference presentation, Big Data Driven Labor Scheduling, we interviewed Greg Tanaka, CEO at Percolata. View the Q-and-A below to see how Greg Tanaka has incorporated predictive analytics into the workforce of Percolata. Also, glimpse what’s in store for the new PAW Workforce conference.
Q: How is a specific line of business / business unit using your predictive decisions?
A: Percolata is focused on helping Specialty Retailers optimizing their sales associate in terms of their selection and scheduling. Our solution is used by store operations to increase revenue while keeping labor budgets in check.
Q: How is your product deployed into operations?
A: Our solution consists of several components. To get the labor demand signal, we use our plug and play sensor. To get the labor supply signal, we have a mobile application for sales associates to give their availability. These signals feed into our predictive machine learning algorithm to forecast the labor load during the next scheduling period. The store manager would then review and publish the auto-generated schedule.
Q: If HR were 100% ready and the data were available, what would your boldest data science creations do?
A: Workforce management in the physical world is incredibly gut-feel vs. data driven. As the cost of acquiring this physical world data drops, most decisions would become data-driven as with online marketing is today. This will lead to a more productive and happier workforce.
Q: When do you think businesses will be ready for "black box" workforce predictive methods, such as Random Forests or Neural Networks?
A: These are techniques that we use today. However, our customers are business oriented, and so we wrap this technology with an action oriented solution so that our retail partners can benefit from the technology without having to know the gritty details.
Q: Do you have suggestions for data scientists trying to explain the complexity of their work, to those solving workforce challenges?
A: It is important to always start with the actors and actions vs. the data. This is counter-intuitive for most data scientist, but it is critical perspective to have in order to have a solution that will positively impact the business.
Q: What is one specific way in which predictive analytics actively is driving decisions?
A: In our case, it is about our predictive forecasting engine. We pull in many different data sources like our sensor data, Point of Sales, weather, marketing calendars, etc. By doing this, we are able to come up with a very accurate demand forecast.
Q: How does business culture, including HR, need to evolve to accept the full promise of predictive workforce?
A: People management has historically been very touchy-feely vs. most other areas of the business mainly because acquiring this kind of data was expensive if not impossible. As the cost of sensors drops, and this physical data becomes much more available, HR and operations departments should be open to piloting this kind of technology to see if it can help the business.
Q: Do you have specific business results you can report?
A: Our customers typically get a 10% revenue increase with the same labor budget by staffing the right sales associate and the right number of associates at the right time.