When Rhonda Gass joined Stanley Black & Decker as CIO five years ago, she centralized the IT function to focus on digital excellence. Since then, she’s seen digitization impact everything from the way products are developed to how they are delivered. We recently connected to talk Industry 4.0, data lakes, and why context is everything.


Rhonda, I’m hoping you’ll educate me and our readers about the technology trends that impact the manufacturing sector today. What’s going on in the Stanley Black & Decker world?

Well, here’s the backdrop. We're turning 175 years old this year, and we have an incredibly rich heritage built on that longevity of serving our customers. But the manufacturing operations have changed quite a bit over that time period. Many trends in technology—cloud, IT, robotics, etc.—are impacting us right at the heart of our business.

Today, our goal is for Stanley Black & Decker to be a digitally-innovative company, one capable of leveraging all of those new technological advances to better serve our customers.

What does a digitally-innovative company look like?

We’ve always been very invested in digital technology from end to end. One example of that focus is the Stanley Fulfillment System, which we have updated and now refer to as SFS 2.0. This system was initially focused on lean manufacturing, working capital turns and those types of capabilities.

But now we’ve evolved beyond lean principles as you might apply them to manufacturing and operations to expand those principles to other areas of the business and encompass things like digital excellence, commercial excellence, and functional transformation. We’re embracing Industry 4.0, the next phase in the digitization of the manufacturing sector driven by technology advances in compute, connectivity, data, and analytics. And those initiatives, importantly, focus on driving value for our customers.

twitter logoWe’re embracing Industry 4.0, the next phase in the digitization of the manufacturing sector driven by technology advances in compute, connectivity, data, and analytics.Rhonda Gass CIO, Stanley Black & Decker 

If you think about our manufacturing facilities, traditionally, we've had automated equipment and machinery, but that equipment and machinery have not been connected to each other in a systematic way.

As we begin to connect all of those machines inside our factories, we're able to automate in ways that we've never been able to automate before. We're able to learn in ways that we've never been able to learn before. And that allows us to improve cost and become more efficient, which provides value to our customers. It also allows us to glean insights from our customers in ways that we've never been able to before. We can not only give them what they want when they want it and how they want it, but we can solve problems in completely new ways.

Industry 4.0 is the beginning of the fourth Industrial Revolution. And it really is all about technology coming into the manufacturing environment to connect equipment and automate processes in the manufacturing area. It’s about connecting robotics and IoT-enabled machinery with intelligence and insights that allow us to streamline our production capability within our manufacturing facilities. We envision fully automating our 100+ manufacturing facilities, where it makes sense, over the next five years through our Industry 4.0 initiative.

»Related content: Stanley Black & Decker To Open Advanced Manufacturing Center of Excellence in Downtown Hartford, PR Newswire

Automation is inarguably changing your environment but it also sounds expensive. I'm curious, how do you pay for those new systems and connections? How is transformational innovation funded in your company?

We actually have a very disciplined approach. We start by creating a strategic plan every year that looks out three to five years. We develop strategic plans for every business unit and include how IT can help enable those plans. From there, the IT function develops a strategic plan that rolls up the business unit requirements but looks out a little further than the specific request.

Here’s an example of how this works: a business unit might not understand how their requirement impacts our collective network capability or costs. But by thinking about the requirements from a cross company and enterprise IT perspective and understanding how technology is leveraging more and more of the internet versus on-premises type applications, we’re able to justify adoption of SD-WAN (software defined wide area networking) over MPLS (multi-protocol label switching) technology. We’re able to be more forward-thinking about technology and the impacts on the business for the longer term.

Once we’ve got the strategic plan with a three to five-year outlook, we then translate that into investments. We apply a rigorous investment prioritization methodology used across the company in which we line up investments, look at the return on investment, prioritize, and determine where we draw the line. The predisposition of our company is to be very focused on innovation and technology.

Things like digital excellence, our Industry 4.0 initiative, the setup of what we call our Exponential Learning Unit within the company, these are all areas we know ahead of time that we want to fund.   

You may be asking, what exactly is an Exponential Learning Unit?  Well, it is our newest step in driving innovation for the company.  We think of innovation as having many layers:

  • Layer 1 is Innovation at the Core.  We have been very successful through the years at this level with all our business unit engineering teams innovating their products and solutions to better solve customer needs. 
  • Layer 2 is Breakthrough Innovation.  Over the past several years, our business units have dedicated small teams, located in separate locations, to innovate and experiment around “big” opportunities.  If successful, these innovations get rolled back into the product teams for commercialization.  But, there is some innovation that needs to occur outside the core product teams that may drive new business models or adjacency offerings that might not be a direct fit for commercialization within a business unit that has quarterly goals and objectives. 
  • That’s where Layer 3, our Exponential Learning Unit or Elu, comes into the equation.  This is a new organization, headquartered in Silicon Valley, focused on disrupting our businesses with a startup mentality.

What about ROI? How do you justify or show return on investment for the dollars that you spend on innovation? What are some of the metrics that you use?

Honestly, there won't always be hard, concrete productivity or cost savings metrics that we're going to realize in a year. In some cases, we’re betting on the future. For example, we believe that there's a lot of opportunity in Industry 4.0—not only for revenue, but for increased productivity.

However, we're not banking the seed investments on immediate cost savings and productivity gains. We’re investing in these things because we know that they will bear fruit, even if there aren’t any hard metrics in Year 1 around that activity.

Once an investment is locked into our three- to five-year roadmap, with a list of projects we’re delivering against, it’s cost, risk, and value that are the measures we watch most closely.

How is all of this innovation on the manufacturing floor going to impact customers?

It's ALL about driving value for the customer. When we think about Industry 4.0, we’re thinking about driving productivity, which means we’re better able to deliver what customers want, when they want it, and how they want it. We get closer to the point of impact. 

As an example, with specific machine data, we are better able to deliver quality at each step in the build process instead of waiting for a quality test at the end of the line.  All along the way, the connected machinery can provide valuable insights as to the quality of the product as it reaches the end of the line.  And, as we all know, it’s much more effective to find an issue early in any process, reducing cost and creating a better customer experience.

If you compare what you are able to do now to the ways in which you were able to tie product development to customer delivery 20 years ago, what are the biggest changes you notice?

You bring up a great point, and that is the connection between engineering and our manufacturing operations. In the past, it could be quite a lengthy period of time before we understood how an improvement to the design of a product could facilitate a more streamlined manufacturing process. With the innovation we envision for our factories now, we'll have a real-time understanding of how a product design or product feature set could be changed to optimize manufacturability or how manufacturing may need to change to optimize for an engineering design.

For example, as we automate and apply analytics against our manufacturing processes, we’ll be able to leverage data and insight to understand opportunities and move much quicker to feed that information from the manufacturing floor back to our engineering teams. Not just the end result but the in-step process metrics all along the way.

Okay, so automation is a big trend for manufacturing. What else? Are there other trends that have your attention? I know I’ve heard you speak about “data lakes.” What the heck is a data lake?

Right. Well, data is recognized as a key value driver for the company. And as we automate our factories, we're going to be generating more and more information. It’s just a fact that any time we bring technology in, we create more data. Because we're preparing for the data we’re going to generate, we're also investing in the “fishing” capability needed to understand what is and what isn't valuable.

A data lake is a data store or warehouse but, unlike in the past where the relationship among the data elements in that warehouse were well understood, in a data lake, the relationship among the data elements is not well understood at the outset. It’s this large data store of potentially unrelated data. You need data sciences techniques to "fish" in that data lake to gain insight and generate valuable relationships you may not have known existed.

We’ve established a data and analytics team that can fish in our data lake. The focus is not only on optimizing our internal operations, which is certainly a key driver for taking costs out, but also to drive that customer and end-user value up.

You have a lot on your plate right now in terms of fulfilling the CEO's digital innovation mission. What are your thoughts on what's coming next? Are you thinking ahead about technologies or innovations that you haven't tackled yet in your IT environment?

There's plenty that we haven't tackled. You know, when you're running an enterprise, particularly one that's 175 years old, there's a lot of work and engagement just to keep the trains running on time. We've not yet taken full advantage of the technology that's available to us today to do that.

That said, there's a huge opportunity with what's at the forefront. We’re taking advantage of innovations such as in-memory computing to be a catalyst for looking at the ERP programs we have underway to move from batch processing to real-time processing. If you think about a business process that's been automated in a traditional ERP system prior to in-memory computing, it would run a job, take the results from that job, and run the next job, and so on and so on. In that scenario, a manufacturing build plan, as an example, is computed over many hours of sequential job runs.

With the application of newer technologies, you can completely transform the way the business process works, running not sequentially but in real-time. You can evaluate your supply plan based on current dynamics or tie your demand into your factories based on the most up-to-date data versus waiting on a batch job run at night. That changes your decision-making in a powerful way.

A similar example is the financial close process. Instead of being a sequence of run this, run that, make this entry, close that entry, what if you were closing your books in real time every day versus only at the end of the period?

We have many programs taking advantage of innovations like in-memory computing underway that have big implications for our business.

Switching gears a bit, I’m curious: why did you choose technology, or did it choose you?

I chose technology, and I chose it because it was in a math-related field. I had performed well in math throughout school but technology offered something new and different. When I started out, technology was a pretty safe career choice too, an area in which you could always be employable. At that time, personal computing and client-server type architectures were being introduced, now you know how old I am, and the opportunities seemed endless. By the way, I knew nothing about these architectures when I decided I wanted to major in Computer Science.

What I found, though, is that technology was all about solving puzzles and problems in new ways and using different languages. I was immediately fascinated. No offense to anyone who loves reading a book and writing an essay about it, but I found technology much more interesting.

No offense taken! How did you become successful in this field?
Hmmm, I guess I was never infatuated per se with the technology itself but I loved the “why” of technology—how it could be used and why it was useful in solving a particular problem. In retrospect, I believe that has paid a lot of dividends, in that it's not about technology for technology's sake, but technology for the sake of driving value, reducing risk, or improving productivity.

twitter logoIt's not about technology for technology's sake, but technology for the sake of driving value, reducing risk, or improving productivity.Rhonda Gass CIO, Stanley Black & Decker 

I started out on the product side, developing products that would be sold and delivered to customers, and I can remember always wanting to understand why a design shift made sense or why certain software should be incorporated. I wanted to tell the story and sell the investment. Being able to translate technology into business speak is something I attribute to being successful in the technology space.

What was the best professional advice anyone ever gave you, and did you follow it?
I think the baseline is “do your job well.” But I also received some advice once about knowing the context for why you're doing what you're doing. What's going on in the business, what's important to your leadership team right now, and what's the strategic direction of the company are examples of context. It’s very important to know how your role aligns with that direction.

IT is all about collaboration and transparency, which is why I think the TBM (technology business management) discipline is so important. IT is becoming a larger and larger enabler of company strategy, and we need a way to collaborate and provide transparency around the value we’re enabling. It’s not always perfect, but the more we can be open and honest about the value drivers, the more we know our strategies marry up to what's important for the company.