Bringing data and process together – The future for Process Improvement: Interview with K2’s Rob Speck

PEX Network recently spoke to K2’s Vice President, Global Services, Rob Speck for our industry report, 'Drive strategic performance through Process Excellence'. The conversation took an exploratory look at what the future of process improvement might hold, including the direction data & analytics might take us, as well as how businesses can avoid becoming disillusioned with these new techonologies.

The conversation offered up key insights and we thought you'd enjoy the conversation. We hope you enjoy the interview below, and when you're finished, don't forget to grab yourself a copy of the report too.

K2 Vice President, Global Services, Rob Speck

PEX Network: Why do you think companies are starting to look to invest in big data and analytics in the year ahead? Why now?

Rob Speck: I think it's a combination of factors, including pervasive connectivity devices that send data wirelessly about everything: you've got machine states, customer locations, atmospheric conditions and on and on. You basically have all of these devices sending massive amounts of data. Today, we can monitor almost anything with embedded sensors that simply send data at unprecedented frequencies. If you couple those trends with ever-cheaper costs of storing data, we have a world full of data orders.

When we look at that exponential growth you can store in the enterprise, we can see that there's value to having tools that can understand what's going on, perhaps trends, correlations, patterns, that can actually help aid in future decisions.

PEX Network: How do you see big data and business process management sitting together?

Rob Speck: It's still a very early growth stage. There are a variety of organizations that have technologies that can handle data flowing in using event-enabled processing, using services-oriented architectures. You've got things like in-memory processing. And you have other organizations that are storing everything that is coming in. Regardless of your architecture, regardless of the way you're handling the big data challenge, at a certain point you basically want to take action.

If you’re a bank, for instance, you might see an inordinate amount of password changes with your online account. A certain level might pass a specific acceptable threshold, which then triggers an alert to investigate as maybe there's potential fraud activity hitting accounts.

Next, you want some kind of action. It may be completely automated, like freezing the password change function across your system so no further changes could happen. But you may have other more complex set of activities that are manual as well. You may have roles in the organization that are alerted to specific human tasks that may be taking place, perhaps exploring the root cause of this specific suspicious condition.

In short, when we talk about value of big data and various technologies, at the end of the analysis you want to trigger a process. And this is where we've seen our technology become an important part of harnessing the power and value of big data.

PEX Network: Now, there's always a risk with new technology like big data that companies just jump on the bandwagon and then become disillusioned when the reality doesn't live up to the original expectation. Do you have any advice for how process improvement professionals can help ensure that their companies don't fall into this "trough of disillusionment" with big data or any other technology investment?

Rob Speck: I've seen that curve that Gartner draws out, and it does happen with nearly every technology wave. In my view, it's all about the business drivers: what are you trying to achieve? Where you've identified opportunities in the business, how can insight into things like customer behavior, operations management quality, demand generation, help these things be improved?

I've seen companies like Federal Express use environmental monitoring to ensure biological samples stay within a necessary temperature range during transport from clinics to labs for testing. For this instance, they knew that they had a need to monitor conditions more accurately and with a constant flow of data monitoring because that would reduce the incidents of fault, which could ruin a shipment, which in turn can cost the company millions, of not just lost revenue, but also lost customer satisfaction and loyalty. So once you understand the business case and that business case is there, as with any technology, it's about taking a pragmatic approach.

Another example is Microsoft. They started in one specific business area and after proving these technologies, the architecture, the approach, they moved to another business unit and so on. One of the impressive things I've seen working with Microsoft is they approach every new technology in a sensible way and I've never seen them take a boil-the-ocean approach. They realize the value quickly, expand, take a step back, look at how to leverage that across business units, and then centralize if, and only if, it makes any sense.

So in short, I'd say use technologies that allow you to gain value in just a few months. Stay away from massive platforms that promise the moon. Do that, and you should avoid that trough of disillusionment.