Just like people, organizations can have intelligence too. “Workplace intelligence” describes things like culture, climate, leadership, and employee engagement that create a great place to work–and deliver positive business outcomes.
Horizons by SAP talked with Ryan Fuller, corporate vice president of Workplace Intelligence for Microsoft Corporation, about the meaning of workplace intelligence, the technology tools needed to develop it, and the trick to using data-driven insights securely and with trust.
Q: The term “workplace intelligence” is relatively new. How would you define it?
A: Overall, it’s about working smarter, not harder, but not just at an individual level. We want to find ways to make the whole organization work smarter. It’s often not clear how to do that, because it’s hard to understand how the things hundreds or thousands of employees do each day add up to the results that companies actually measure.
How do you get a clear picture of what’s happening?
You need to be able to zoom way out to be able to see the whole picture. That requires the right kind of data, so you can identify the patterns that lead to better outcomes. Often companies spend huge amounts of time doing things that don’t add that much value. How can we stop doing those things and devote the time to more impactful things? Or give our employees more of their time back, so they can live fuller lives beyond work?
The idea of continuous improvement has been around for a long time. Yet in many organizations, it feels like we’re going in the wrong direction.
Workplace intelligence helps us create some new patterns that reverse that trajectory. It gives everybody the tools, visibility, and data to know how to work as effectively as possible in the shortest amount of time possible.
What is the first place to start experimenting, once you’ve freed up some capacity?
We like to look for bright spots–those parts of the team or organization that consistently outperform their peers. Oftentimes, leaders know that a given team is great, but don’t know why. Usually the team doesn’t know either–they just know that they do good work.
How do you figure it out?
When we focus on the behavioral data, we can start to see patterns. Let’s say you learn that the team spends 50 percent more time with customers than any other team. You then learn that happened when their management decided to spend less time on forecasting and internal processes. Although it’s a simple change, it’s massively impactful in terms of how people have been able to spend their time. And now you have a proven pattern within your own organization that you can scale.
Success breeds success.
Exactly. If you can find areas that are working, you can then figure out why and how it happened and scale it out. Next, you must spot opportunities to improve and enact those changes elsewhere. Companies get into this continuous cycle where people identify opportunities, use data to figure out a better path forward, and then enact change programs. Then they measure results. The idea is to encourage a culture of experimentation and learning.
What kinds of capabilities or functionality are needed to execute this type of program?
My team specializes in compiling passive, aggregated, and deidentified data automatically generated from e-mails, meetings, chats–all kinds of collaboration tools that companies use. We turn that data into a behavioral data set. From that data, you can understand how people spend time, which teams are spending time with other teams, and what people’s networks look like. You can derive all of these very interesting insights that are really hard to measure in any other way. As a result, company leaders can get a full understanding of exactly how that process works. They can tell whether it is efficient or needs to be improved.
In your research and your work with customers, have the analytics revealed any surprises?
Very frequently, actually. For example, sales leaders often say that sellers should spend most of their time with customers. We can look at the data to see how teams are working, how they engage with customers, how much time they spend on different activities, who they bring to the meeting, and what
their networks are like. You can also see which patterns correlate most with revenue generation. And top performers do tend to spend more time with customers. But even more predictive of better performance is that top performers have larger internal networks–meaning that they engage with more people within their own company more frequently than others do.
Why is that?
When you think about it, sales is not a one-person activity. For example, you must know the right specialist to bring into a customer meeting, or the person in legal that can push through a contract quickly, or how your product team is thinking about the road map. In fact, your ability to bring everything that your company can offer to a customer is really contingent upon your personal network. That takes work and a lot of time. If you spend 90 percent of your time with customers, how are you going to know anybody at your company?
So, how do people react when they get these insights?
Sales leaders initially find it counterintuitive that internal network is so important. Once they see the data, they can quantify how that networking accelerates the ability to produce revenue. Then they understand the value of this intelligence.
What kind of tools are available to help companies develop more workplace intelligence?
It starts with identifying new insights from a behavioral data set. That’s what Microsoft Workplace Analytics offers. Instead of relying on surveys, anecdotes, and consultants to know what’s happening, the technology provides an objective, always-current data set. You can set new goals for what you want to achieve and then operationalize it by putting in place some lever to drive change.
How would that look in your sales example?
Management could decide that employees need time to develop those personal networks. Perhaps they redesign sales territories to make them smaller. Then we measure to see if that has an impact. The data helps you know when to make a change. And then you can operationalize it using traditional management levers, like a dashboard.
Where do the employees’ decisions come into play?
The next layer is addressed by products such as Microsoft MyAnalytics. Let’s say you realize that teams with higher employee satisfaction have managers who spend more time in one-on-one meetings with their direct reports. This context-aware technology provides employees with individualized, personal insights that help them accomplish their goals. Maybe a calendar app sends a message suggesting that a meeting with your direct report Brian is overdue, and it notes that you’re both free tomorrow at 2:30. The software prompts you to send a meeting invitation. We try to engage users at just the right moment with helpful information that will help them be more productive and engaged.
What different types of assistance can employees benefit from?
Some solutions make it easier for a user to do something they already intended to do, like automatically filling in the rest of an e-mail address as they type. More advanced software proposes things that the user didn’t think about but would have done, like scheduling that meeting with Brian. The most sophisticated is software that introduces actions the user wouldn’t have considered, because they are designed to meet some larger organizational goal.
You mentioned security and trust earlier. How do you find that balance between providing useful insights and maintaining employees’ trust?
First, flexible privacy and compliance controls allow customers to protect their data. Organizational data is aggregated and deidentified. It’s adapted to country requirements. And the tools evolve based on what customers need. We do a lot of low-scale experimentation and we work hard to solicit feedback on how people are using the software and their reactions. We frequently change the words we use on prompts. It’s amazing how the same nudge, worded slightly differently, can be received differently.
There’s a real risk-reward equation that people apply to technology.
That’s true. People may inherently distrust the technology, but they start to feel differently if they’re getting value from it. That said, we need to earn trust by making sure that we’re not doing any of the things that people worry about. As we earn trust, hesitancy shrinks. But that’s not something you can do overnight. We think about it every day, with every feature. Because we know crossing that line is not easy to uncross. We want to help organizations and employees be empowered to spend time in the most useful ways, and as we do that, the value grows and grows.
About Horizons by SAP
Horizons by SAP is a future-focused journal where forward thinkers in the global tech ecosystem share perspectives on how technologies and business trends will impact SAP customers in the future. The 2020 issue of Horizons by SAP focuses on Context-Aware IT, with contributors from SAP, Microsoft, Verizon, Mozilla, and more. To learn and read more, visit www.sap.com/horizons.