The symphonic enterprise has been saved
How do we work alongside bots without resenting them? And can there be poetry in the technology enterprise? Bill Briggs discusses these and other technology trends of 2018.
Tanya Ott: Artificial intelligence, bots—the question isn’t if but when they’re coming to a cubicle near you.
If that happens, how do we make sure people are comfortable with what we're doing? And some of the tactics here are, if you're working side by side with a bot, for example, simple things like naming the bot. Calling them—you know, fill in the blank—George Washington? [Since] I'm a Notre Dame fan, calling them Lou Holtz. Just a way to personalize that interaction is an important part of the equation.
I’m Tanya Ott, and this is the Press Room from Deloitte Insights. Today we’re talking about reengineering IT and using new tools with humans in mind. Bill Briggs is chief technology officer of Deloitte Consulting LLP. Each year Bill and his team publish a Tech Trends report, which
explores the big things coming in the next 18 to 24 months. Even if you don’t work for a company that’s on the cutting edge of technology, I think you’ll find this conversation really interesting because this stuff is going to shape the workforce of the future in really significant ways. Plus, it’s kind of cool to get a preview of what’s to come.
This is the ninth annual Tech Trends report, and Bill says there’s an overarching theme.
Bill Briggs: Yeah, Tanya, it's the symphonic enterprise which makes some of my more cynical CIOs chuckle, but it wasn't just meant to be poetic. It's really shifting the emphasis in what we do. We always try to talk about the so what, not just the what, of the technology, but in reality it's how they come together. So the symphonic enterprise is putting the emphasis of the controlled collision between the trends, and then filling in the blank: within the business, in the market, for a customer. So the whole is more important than the individual instruments being played.
Tanya Ott: We're going to take a look at some of those so whats and now whats in just a minute. But I think kind of underlying what you're saying here is that, in the past, companies were looking at domains—they were looking at digital or analytics or IT in silos. And now they're looking more holistically, and it's all those disruptive forces that are happening in the world around them that are forcing them to do that, I guess.
Bill Briggs: Yeah. The first trend is reengineering technology—the fundamental transformation the IT department. How do we organize, how do we prioritize, budget. But in that, it's the elevation from IT to capital T technology, which is as much talking about the lines between back office and operational technology and even the product-facing, customer-facing, market-facing technology. The divide between those is false, if it exists at all. So how do we elevate? And I love that, because it shifts the CIO discussion and the broader “how do we invest in tech” discussion [away from just] “How do we be more operationally efficient, how do we drive efficacy of our existing systems?” [and turn it into a] discussion of “How do we fundamentally rethink how work gets done inside the enterprise? How do we fundamentally rethink customer engagement? How do we fundamentally rethink our products and services and offerings? How do we even fundamentally think about our business model and our industry and the boundaries between our sector and our competition?”
With all of that in front of us, we have to get it down to tactics. The reengineering tech chapter is all about, let's make that real. So here's a prescription for top-down thinking about IT, budget, oriented around customer, around business outcomes, around product, and actually organizing teams that way instead of around technical skill sets. How do we change our delivery and operating model—agile, not as a hobby, embedded in the DNA? We're driving toward iterative, value-creating, smaller returns of investment. We're moving toward dev ops, not just [in a technical sense], but as [a philosophical way] to think about our IT operating model. And then the bottom up: If we want to do those things right, we've got to make investments that maybe we haven't done enough with—so, infrastructure modernization and migrating to the cloud. We've got to think about autonomics and put in place the tooling to allow that speed to happen, and a different approach to architecture and platform. So it's nice that in the [leadership], they get this idea of, yep, what we've been doing isn't enough. We need more, and we have to change the way we approach getting value out of our technology investment. At the bottom up, you can speak to the CTO, the head of infrastructure, the head of apps, to say these very specific things that we need to change to be ready to do the top-down.
We saw for a while the investment would be, hey, let's simplify our infrastructure, let's move to cloud, let's modernize our application set. But it wouldn't have the commiserate top-down: While we're doing that, we can really turn our IT department around and basically talk about delivering in a different way. Faster, closer to the business, with design as a discipline in the center of it. And the flipside is if we try to do that kind of a top-down transformation without the enabling tools and platforms behind it, there's only so much we can do. The best intention, the most compelling strategy, at the end of the day it's a nice flywheel, there's a reinforcing loop between the two. They have to come together.
Tanya Ott: So you've got a couple of examples that you cite in there. You give an example of a food marketing and distribution company. You've got a German telecom operation. And you have a fitness, nutrition, and weight loss program. Let's talk about one of those. Maybe you could give us a case study looked at.
Bill Briggs: Yeah. The fitness program moved from DVDs selling streaming services. Their whole business was shifting to digital. That was the heart of the problem. They looked at it and said, “The pace of our IT delivery has to be in days as new features get rolled out, and we have to completely rethink customer engagement, and we have a pretty traditional IT staff.” So there was a huge investment to say, OK, let's move to cloud. Let's move to tools to automate the full life cycle of IT delivery. At the same time, we're to put teams against product lines. And so the business is directing the backlog of ideas, of how do we continuously improve and innovate, not a yearly budgeting cycle that goes down and gets fit into programs that have quarters or years of execution. Teams are completely dedicated and ready to respond. And those two together, as they pivoted the business, they point to, if we wouldn't have made those technology investments in the infrastructure and in the way our people are organized, how they're delivering, it wouldn't have worked. So it's a great, talking about a “top of the house” business strategy discussion that led itself to a fundamental reimagining of IT.
Tanya Ott: When you use the word reengineer, do CIOs freak out? I mean, is that a scary word?
Bill Briggs: Yeah! I'm glad you asked. We have a skeptic's corner in every chapter where we actually hit on that. And the intent was to say, listen, it is deliberate. So trying to hearken back to the days of finance and supply chain, this has to be intentional and deliberate and look across all of IT. By the way, we've done it for every other function; we haven't done it for (insert your favorite cobbler's children euphemism there). So it does get their attention. I think, as we break it down and say, now this doesn't have to be a 9-, 10-, 12-figure investment, you could do it and break it down into chunks so you can prove what we're doing and actually deliver value along the way. But we don't want to shy away from [the] very significant change from what it was before. So there is some reaction. We try to temper the knee-jerk reaction to it. But it was done intentionally. It needs to be delivered. It needs to be holistic. It needs be transformational—and so we thought that's a pretty good word to summon those thoughts up.
Tanya Ott: So lightning round here. What are the steps that CIOs and companies need to take to reengineer their IT? What are the big ideas?
Bill Briggs: Go bottom-up. That's easier. So virtualization across the stack: server and storage and network. Infrastructure as code. Make that the standard. Move the containerized, to allow workload overtime to be able to move to the cloud. And likely that's a part of the immediate steps: How do we get more out of what we're doing into the cloud? This idea of automation across the IT delivery cycle. So how do we apply RPA, how do we apply machine learning inside of IT? We call it autonomics, but it's things like environment provisioning, things like test automation, things like helping automatically deploy into production. All those kind of feed into that. So there's specific things on the bottom-up which are familiar, but part of the story is they have to be done together. And then the top-down is how do we think about the portfolio of IT spend and more strategically disposition it? How do we organize our teams around product and customer and business outcome? How do we think about the skill set that we need, including behavioral design and some of these new infrastructure engineering and data engineering? [If] we invest in the bottom up, it actually elevates the skills that we need.
And I love, Tanya, this idea of tech fluency. Anyone that works in technology has heard, over the years, you have to be more business savvy. How do you speak the language of the business as a technologist? Which is true, and we all need to do more of it. So this is an "and" not an "or." But we've also found that business executives need to be more tech savvy. So it's flipping the script a little bit. And we've found that this education of what's happening [can’t be just] a consultant's tech trends report, or you sat next to a vendor on a flight. Informing the CEOs’ perspective, giving them enough detail to really know what matters and why in emerging technology, but also helping educate the business of the need to reengineer tech, including some of the bottom-up bits that might historically have been completely the purview of the CIO or the CTO. Get the organization at large to understand why infrastructure modernization is important, not for cost take-out but to create a foundation to be able to drive innovation and growth.
Why is app monetization important? Technical debt is not something that the business can look at the hole in the IT department side of the boat and say, we're comfortable, we're all going to get wet. The fact that there's a hole in that side of the boat is all of our shared responsibility to do something about. So this tech fluency is helping inspire tomorrow and get the business more savvy, but also this idea of making them understand what is going to take to get there from today, which is a big part of the second piece. So I loved those together, and we're seeing that more and more via board and the CEO level and a mandate [that] we're going to drive tech fluency, tech awareness. Call it a digital academy, call it a tech college, call it whatever you want.
Tanya Ott: So that's technology. The next chapter you title "No-collar workforce." What's that?
Bill Briggs: Ah, yes. So for years we've been bullish on the collection of machine learning and AI (artificial intelligence) and RPA (robotic process automation) and bots. We use cognitive as the umbrella that covers those different domains. We've been bullish on cognitive and what it means in the business, across business processes, cross function, for years, and we continue to be. So this one is built upon what the potential of cognitive is. Now with that, we're seeing folks that are invested— they're dealing with what are the cultural implications, what are the talent implications, what are the HR implications to an increasingly automated workforce? Which could be, we've got augmentation, and a big percentage of what we're seeing is not jobs being removed or replaced, but they're being augmented. So [for] the rote repetitive tasks that people were doing, it's actually helping so that they can have a higher order. So if it's a claims administrator in an insurance company, they have all of the history of the individual patient, the clinical history, the case history, and policy history all ready for a disposition, instead of the 15 or 20 minutes it took them to pull that all together.
Tanya Ott: So the idea behind this in whatever industry is that if you can take that really basic rote stuff out of their hands, give that to automation or to bots or to whatever it might be, artificial intelligence, it frees up humans to do the things that humans do best.
Bill Briggs: Exactly. With judgment, with intuition, with creativity, and with more purpose. But the trend is saying, okay, if that happens, how do we make sure people are comfortable with what we're doing? So there's a change management exercise. If we're saying you're going to elevate what you're doing now because some of rote tasks that you used to focus on being done for you, then how do we help make that a graceful transition.
Tanya Ott: That's a highly emotional thing to deal with.
BILL BRIGGS: A hundred percent. Some of the tactics here are, if you're working side by side with a bot, for example, simple things like naming the bot. Calling them—you know, fill in the blank—George Washington? [Since] I'm a Notre Dame fan, calling them Lou Holtz. Just a way to personalize that interaction is an important part of the equation.
Performance management—if you don't consistently enable your workforce with these tools, you better make sure when it comes down to measuring performance and in doing incentives that you've taken that into account. Because if you're just saying, how many cases are closed or how many incidents are resolved, if one individual has an augmented tool doing that at the speed of machine while the other individual is left doing it the way they've always done it, obviously there's not parity there.
So there's an interesting collection of things on augmented work: How do we think about culture and talent? The interesting bit is also for the bots that are being deployed that are more stand-alone: They are doing work without that human intervention, [and] there's a similar bit of, “How do we think about the human resource dimensions of these resources that aren't human?”
Tanya Ott: What do you mean by that?
Bill Briggs: This is the pass-the-Scotch moment. How do we on-board? Is that a technical deployment, or is it more of an HR event when we're ramping up? It doesn't have the same paperwork and benefits perhaps, but there's still some interesting things. Do you give them an individual ID in a system, or is it a system ID? Well, it better be an individual ID, because if tax law changes and we have to go back and account for the work that's being done by a bot, I need to be able to track that individual level by level.
TANYA OTT: Is that a thing? I mean, is tax law potentially going to change, and we're going to have to track stuff by bots?
Bill Briggs: It's been rumored.
Tanya Ott: Really?
Bill Briggs: It will be country by country. Here's an even more interesting one. If we have a bot that’s a lone decision-maker, or if it's doing that claim authorization and it makes a mistake, is that a technical issue like a typical bug or defect we track? Is it a training issue where we would go back to the human that actually guided the machine and taught them the thresholds of what was acceptable or not? Or is it a performance issue with the bot? What's the disciplinary action you take with the bot? Some of these are questions that we're exploring.
Here's one that I found a bit depressing, but there's a reason that the company is doing it. They found that having a machine that was tireless and unerring was actually disconcerting to the human workforce who were working side by side [with it]. So they've been looking at actually coding in some fallacy to make it a little bit more humanlike. Perfection is very unsettling when you sit beside it in the cubicle. There's an interesting philosophical discussion about it. But think about the guard-duty problem of how do you make sure that you stay alert. If my whole job is to validate if something has been denied by the bot, in the insurance example, if it doesn't make a mistake, every once in a while I'm quickly going to become very complacent in my review cycle. So there's a reason for this as well, besides just it makes me feel better. It actually is necessary so you don't fall asleep at the proverbial wheel.
Tanya Ott: Brave new world, huh?
Bill Briggs: Yeah.
Tanya Ott: We've got just a couple minutes left. One of the other sections you talk about is, if you love your data, set it free.
Bill Briggs: Yep. It's the most important asset we likely have. I don't like the "data is the new oil" metaphor, because oil is a resource [that] once you use, it's destroyed, and it can only be used for one purpose. Data is a lot richer than that. It has a lot more potential, but most big companies, most big government agencies, they haven't done data well. So the idea is we want it to be free. We recognize the value. It should be shared wherever it's needed, and potentially we can monetize and expose it to business partners or ecosystems. But we can't because we haven't done things like data management, data governance, and master data well. Up until the last few years, it's never been easier because most of the data was data that we owned, it lived within transactional systems and well-formed relational databases. Now we're moving into this world of dark analytics, with video, audio, images, machine data, biometric data, and you name it. So, the message here is a message of hope. It's that the same things that we're using to drive insights in the business—in machine learning, natural language, automation—can be applied to this data problem. So we can use it to have a better, dynamic way to ingest data, to understand data, to categorize and classify relationships of data to determine where it should be stored, who can have access to it.
And the kicker here is that's important inside-out. Any enterprise that does this well, it's a competitive advantage. It's also important outside-in for things like the EU GDPR (General Data Protection Regulation) that's coming in May. If global regulations change, and we have to be able to report on data privacy, data residency, it'd be very wasteful to launch a Y2K-like study for compliance for each one of these. Because we know there's going to be more. So GDPR is in the headlines because it's so imminent. But how do we get a better answer? And by the way, the things we do for the outside-in [functions] can also help us for this inside-out problem of, how do we understand data and set it free?
Tanya Ott: So many questions. So much changing on this landscape. You've got a 150-page report here that is chock full of scenarios and case studies and analysis of risk and advice for what companies should do to start. Thank you so much for joining us today. You're going to be back again with Tech Trends 2019?
Bill Briggs: We will! Tenth year. We'll try to do something special for the milestone. Thanks, Tanya. It's always great to talk to you.
Tanya Ott: Yeah, you too. Thanks, Bill.
Tanya Ott: That’s Bill Briggs, Deloitte Consulting LLP’s chief technology officer. The 2018 Tech Trends report is available at deloitte.com/insights. Coming soon: We’re going to take a deep dive into behavioral economics with conversations and insights from researchers and thought leaders at an event called Nudgeapalooza. Here’s a little tease:
There are controversies. There are questions marks. There are issues. People talk about ethics. People talk about the sustainability. People talk about the applicability in different contexts. But that’s what makes this even richer and more wonderful to examine.
I’m Tanya Ott for the Press Room. Have a great day!
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