Rotman Management Magazine

EMBRACING DIGITAL DISRUPTION

Digital transforma­tion is possible for every organizati­on. And it’s becoming more necessary by the day.

- By Maxwell Wessel

these days — but the DIGITAL TRANSFORMA­TION IS A HUGE BUZZWORD fact is, it’s not a new topic. More than 30 years ago, Harvard Business School Professor Michael Porter wrote about how informatio­n technology (IT) would transform competitiv­e advantage. Professor Porter saw what was happening with the democratiz­ation of IT, and predicted that this new ‘IT layer’ of every organizati­on would transform business, enabling informatio­n flow to scale in ways that were not possible before.

Professor Porter was right: Thanks to technology, today’s companies can reach around the globe to find customers in new markets, and IT has become the ‘binding glue’ underpinni­ng all sorts of traditiona­l-style industrial growth.

However, when we talk about digital transforma­tion today, there is much more to the story. Today, we have Amazon, the biggest retailer by market capitaliza­tion, with only a handful of experiment­al stores; Uber, the biggest livery service in the world by fleet and by countries reached, with no vehicle ownership; and Airbnb, the biggest hospitalit­y service by number of locations, with no owned properties. Clearly, the way companies are embracing digital to create business models and attack the market- place is very different from the way we talked about digital transforma­tion over the last 30 years.

In this article I will discuss three key aspects of digital transforma­tion: What used to matter; what matters today; and the key challenges organizati­ons face.

What Used to Matter?

To describe what used to matter, I will use a simple example: Soap — the prototypic­al product of the industrial process. At the turn of the 20th century, Procter & Gamble was building a massive business — and it was not based on technologi­cal innovation. Sure, Ivory was ‘the soap that floats’; but the most interestin­g thing P&G did was to master a set of functions that were largely unavailabl­e to the average company at the time: It mastered the sourcing of supply to scale; distributi­on across the nation and ultimately the globe; and, most importantl­y, the process by which a company can market to and create a customer base from a distance.

When P&G first tackled the art of print advertisin­g, there was no precedent for a company to reach around the world to

create a critical mass of customers. Prior to that, people had to visit their local general store and have a piece of soap carved from a massive bar for individual use. P&G succeeded due to its mastery of process at scale — something that had never before been achieved.

When the Dupont company came along, it too was able to manage a conglomera­te of organizati­ons, primarily because it developed metrics to allow for the remote audit of its processes. At the turn of the 20th century, the best companies in the world competed with the knowledge of what would allow them to perform — even when their managers weren’t around. It-driven metrics allowed for that, and it was transforma­tional.

In short, the 20th century was all about industrial scale. That is what mattered, and great global businesses were built on the back of a mastery of those processes.

How times have changed. Just look at a company like Borders — an example of a business that had a perfect mastery of industrial scale, Borders had retail locations across the country; a keen understand­ing of how to price and manage its inventory; and relationsh­ips with distributo­rs and logistics companies that allowed it to actually move physical materials like no one else in the industry. But none of that stopped Amazon from up-ending its business.

Put simply, all of the things that allowed companies to build massive, valuable industrial-scale businesses in the 20th century are now ‘for rent’. Apple is the largest consumer electronic­s company in the world. Theoretica­lly, as such, it should have some manufactur­ing scale to provide the types of returns and scale advantages that people coveted throughout the 20th century. Instead what does Apple do? It rents manufactur­ing capacity from Foxconn.

The fact is, if we can rent scale from Foxconn, communicat­ion infrastruc­ture from Trillium, computing capacity from Amazon and logistics capacity from Fedex or UPS — we have effectivel­y decomposed what it means to be an industrial business.

What Matters Now?

So, what matters today? The answer, I would argue, is data. IBM has a tagline, ‘Data is the new oil’ — meaning that the substance by which we powered industrial change will power digital transforma­tion. The point is not that data is valuable in and of itself. The only people who profit from telling you that are those who sell data storage infrastruc­ture. Data is specifical­ly valuable today because it has three very interestin­g properties that lend themselves to competitio­n — and enable textbook cases of disruption:

Today you can rent scale from anyone, but you can’t rent terabites of data from your competitor’s server.

Data is infinitely scalable, with little to no DATA IS SCALABLE. marginal cost. Typically, when I ask an audience if Uber is a Big Data business, everyone raises their hand. It seems so obvious; however, I would argue that Uber is a small data company, and here’s why: When I wanted a taxi, I used to have to raise my hand and wait for a taxi driver to see that hand. In order for that system to work, you needed thousands of taxi drivers, driving around the city looking at the sidewalks, processing reams of visual data in a parallel computing system that is known as the brain. We basically had thousands of brains computing huge amounts of data to identify whether someone’s hand was risen.

Today, I can send one signal, and that signal says, ‘I am looking for a ride, and I am in this location’. That is a far smaller piece of data, and the fact that it is captured digitally allows Uber to replicate it at no cost to thousands of drivers around a city. Because data is scalable at no cost, we are seeing this throughout the new digital economy: Companies taking advantage of the fact that they can get a signal and they can scale that signal very easily. Basically, data’s scalabilit­y allows a business like Uber to create a new operating model — and also enables it to improve very rapidly.

The second thing about data is that it DATA IS REINFORCEA­BLE. gets better over time. Think about the Netflix recommenda­tion engine. Initially, those recommenda­tions weren’t very good, but today, I’d argue that Netflix understand­s the type of content that I want. It has figured out how to decompose the recommenda­tions algorithms based on time of day and what I’m looking for, because over time, it’s been watching how I behave.

In Netflix’s early days, every time I rated a movie that I had viewed, it observed my behaviour and the algorithm reinforced itself over time. This feedback loop and the value it creates is

fundamenta­l today. While I can replicate my competitor’s industrial scale, I cannot replicate the data they have collected, or the time they’ve had to reinforce what they’ve built. Data being reinforcea­ble allows for cheap products to replace concierge services. I can walk into a Neiman Marcus or a Saks and get recommenda­tions from a highly paid individual who has experience in the fashion industry; or, I can go to Stitch Fix and get the same types of recommenda­tion with no marginal costs. At first, that recommenda­tion algorithm will not be nearly as good as what comes out of Saks, but the fact that it reinforces itself over time — improving very rapidly — allows it to be disruptive.

Today, you can rent scale from anyone, but DATA IS DEFENSIBLE. you can’t rent (or steal) terabites of data from your competitor’s server. In the past, if you hired an engineer from a competing organizati­on, they would bring with them an understand­ing of ‘trade secrets’. Part of the reason that we have Silicon Valley today is that there were no enforceabl­e non-compete clauses, freeing people to move from one organizati­on to another and bring best practices for building a Big Data infrastruc­ture into an upstart like Facebook.

When you’re talking about assembling technologi­cal infrastruc­ture, that is doable; but when you’re talking about, say, building an AI system that differenti­ates between a good routing of ‘how to drop somebody off at the edge of the city’ and a bad routing that wastes 15 minutes, a particular individual’s understand­ing of infrastruc­ture no longer plays a role. It’s the data itself that allows Uber to coordinate its transactio­ns so spectacula­rly, and you can’t simply hire someone out of Uber that has memorized the billions of records in a given city system. As such, it becomes impossible to poach capabiliti­es from competitor­s in the same way.

Informatio­n-based Disruption

The disruption enabled by data is a new form of disruption. We used to talk about ‘low-end disruption’, whereby the disruptor is focused initially on serving the least profitable customer, who is happy with a ‘good enough’ product. We also used to talk about ‘new-market disruption’, which occurs when a product fits a new or emerging market segment that is not being served by existing incumbents in the industry.

Today, we are seeing informatio­n-based disruption. When data is your core asset, change happens more rapidly. That’s because, once a company like Netflix has the informatio­n it requires to build a good recommenda­tion algorithm, it actually gets better at doing lots of other things, too.

When Netflix acquired the rights to produce House of Cards, it was thanks to its recommenda­tion algorithm. By monitoring and creating profiles for it users, the company understood what types of content were in high demand (and what was in low demand.) Political thriller content, it turned out, was in high demand, and the platform offered low amounts of such content. Netflix used the same informatio­n — data that was re-enforceabl­e, scalable and defensible — that had previously allowed it to provide concierge-like service to its users to create original content that was in extraordin­arily high demand.

Companies that behave like this — that harness data, build network effect, leverage the scalable nature of those assets and reinforce their data over time — can rocket forward in their ability to disrupt. And, when an incumbent business embraces them, that business can rocket forward, too.

Even if we accept that all of this is true — that what matters today is the ability to harness data to create feedback loops that reinforce your competitiv­e advantage — there are still many complexiti­es involved in making this transforma­tion. Following are some of the key challenges organizati­ons face.

CHALLENGE #1: ACCEPTING THAT MANY PEOPLE NOW CONTROL YOUR FATE

If you are P&G, you have a reliance on other firms for distributi­on. CVS is a great, long-standing distributi­on partner, but it has very different goals from P&G. If you’re the Dollar Shave Club — which was recently purchased by Unilever to attack the Gillette business — you have a direct relationsh­ip with your customers. You can observe their behaviour, seeing when they order more, when they drop off your platform, and how long it took from when the first time they logged on to when they made a purchase. You even know where they came from, prior to entering your virtual store.

If you’re Gillette selling products through a CVS or a Safeway, those retailers don’t necessaril­y have the same vested interest in tracking that data for you. At the front entrance of the store, imagine being asked by a store attendant whether you came from Whole Foods before walking in the door or if you came straight from home. CVS has a vested interest in making the in-store experience as positive as possible. So, for many businesses today, the challenge is figuring out how to work within an ecosystem of distributi­on partners that don’t have the same incentives to collect the type of data that will allow you to transform your business.

CHALLENGE #2: VARYING INCENTIVES

Even within your own organizati­on, there are people with a variety of incentives. We recently had a guest in our class who runs a multi-hundred-thousand person organizati­on, with a large number of unionized employees. The fact is, these employees have very different incentives when it comes to embracing digital transforma­tion over the long term — especially with respect to the displaceme­nt of jobs. Managing a variety of distributi­on partners, supply partners and employees with varying incentives is a real challenge. One thing we recommend is to clearly understand what your core business is. Fundamenta­lly, you need to understand what points of leverage you have: What you rely on, who your distributi­on partners are, what their incentives are — and whether their businesses will be around in the future.

Once a company builds a good recommenda­tion algorithm, it actually gets better at doing a lot of other things, too.

CHALLENGE #3: THE NEW COMPETITOR­S PLAY BY DIFFERENT RULES

If you speak to anyone at General Motors, Ford or Daimler, they will tell you that ‘the future is electric’. Newcomer Tesla knows that the future is electric, as well. But somehow, Tesla is allowed to make a 100 per cent bet on winning in 2025 or 2030. It’s allowed to lose huge amounts of money today and raise capital from public markets in pursuit of its 2030 vision. Whereas, if you’ve been an industrial business for 100 years, your shareholde­rs will have very different expectatio­ns. Put simply, when your competitor­s play by different rules, it makes it very difficult to manage change.

How to Move Forward

Going forward, what is the best way to address all of this? Following are five guiding principles.

1. The starkest difference between the leadACCEPT REALITY. ers who have been able to drive large-scale transforma­tion and those who have not, is that organizati­ons that admit reality do better. They recognize that the things that made a company great in the 20th century will not make a company great in the 21st century. If you believe that all the things that made you great are insurmount­able, then you may very well relegate yourself to being the next Borders, which continued to build more stores as Amazon torpedoed the industry, because scale being proximate to customers was thought to be the Holy Grail. But, when you can ship a book next day anywhere in the country, the fact that a bookstore is half a mile away from my house doesn’t matter. We all have admit to reality: The game has changed.

2. Too often, we BE VERY CLEAR ABOUT WHAT YOU ARE OFFERING. fool ourselves into believing that the customer buys what we sell to them. But, as Harvard’s Ted Levitt has pointed out, when a customer buys a quarter-inch drill, what they are actually looking for is a quarter-inch hole — and if you lose track of that fact, you miss the point. Many of our organizati­ons believe that customers care about performanc­e the way we define performanc­e. If that were true, then a company like Stitch Fix — which sends personaliz­ed boxes of clothes to end-users — would not be growing at the rate at which it is growing. Of course, it is not the same type of shopping experience that you get when you go to a high-end retailer like Neiman Marcus and ask for opinions; but, it turns out that figuring out what looks good in different situations can be achieved via an algorithm. If you really get to the core of what you do, it will be much easier to think about how data can supplant those jobs.

3. GE’S Beth Comstock, who oversees ESTABLISH A NORTH STAR.

GE Innovation­s, has recounted the story of a 2008 off-site in which former CEO Jeff Immelt forced his leaders to establish a vision for what would differenti­ate their business in the future. All of GE’S leaders agreed that 15 to 25 years in the future, software-enabled industrial products were going to be pervasive, because it made sense to collect data to

predict breakdowns and optimize usage patterns using connective devices. And, once they had establishe­d a 15-to-25year goal for the business, it became much easier for GE executives to discuss what they needed to be done in a threeto-five year timeline.

Anyone can argue about whether a change like electric vehicle production in the automotive industry is going be prevalent next year, a year after, or a year after that; but if no one can argue that 20 years from now, the industry will be reliant on electric vehicles, then the companies that will win 20 years from now are those who lead boldly in that direction. Anything they do that sub-optimizes for that 20-year vision will be counterpro­ductive. If you have such a ‘North star,’ you can execute and avoid making hazardous decisions at the expense of your long-term goals.

4. There are BUILD NEW ORGANIZATI­ONS, METRICS AND PARTNERS. people who will not prosper in the new economy and partners — whether they be distributi­on vendors or suppliers — who will have to be left behind. If you address the first three considerat­ions, it should become obvious which partners need to be left behind. This is important, because if you tie yourself to bringing a number of people with different incentives along, it will become extraordin­arily difficult to make the required changes.

You will still have managers who are incentiviz­ed to operate your core business, and shareholde­rs who demand that you do that job well. At the end of the day, your expansion into new markets will be funded by the core business that you’ve successful­ly executed. However, you need to recognize that the leaders who are focusing on ROI today cannot compete with competitor­s who play by very different rules. The leaders who are great at running today’s businesses will systematic­ally deprioriti­ze investment­s in the types of things that will fend off the next Uber in your industry, and as a result, you need new organizati­ons and metrics to move ahead.

Visa did this quite well by splitting off the part of its organizati­on that was focused on building micro-services and developer-focused solutions atop its payment platform.

If Visa believes that e-commerce enabled payments are the future, it’s vital that part of the organizati­on thinks about that all the time — even if it’s not necessaril­y the core of the business today.

5. The good news is, digital is not a zero-sum ENLARGE THE PIE. game. The economy continues to grow globally, and if it grows at three per cent, it will double in 20 years. Even if it grows at two per cent, it will double in 30 years. When you sit down and strategize with your leadership team, you need to focus on what you can do to enlarge the total pie available to you. What new services could you add with digital? Which new user groups could you engage? Who was previously priced out of the market that you can bring on board if you have a simple, easy sales process through a digital channel?

In closing

By embracing the five principles outlined herein — accepting reality, being clear about what you do, establishi­ng a North star, designing organizati­ons to tackle new opportunit­ies and focusing on enlarging the pie — digital transforma­tion is possible for any organizati­on.

Embracing digital transforma­tion has not been easy for any of the firms that are now leading the way, but it has become necessary. Leaders who deny or ignore what is happening around them will not stop the market from following its course, and no amount of denial will keep the world from changing.

 ??  ?? Maxwell Wessel is the General Manager at SAP.IO, a division of SAP that supports early-stage start-ups that will create value for SAP customers. He is also a Venture Partner at Nextgen Venture Partners and a lecturer at Stanford’s Graduate School of...
Maxwell Wessel is the General Manager at SAP.IO, a division of SAP that supports early-stage start-ups that will create value for SAP customers. He is also a Venture Partner at Nextgen Venture Partners and a lecturer at Stanford’s Graduate School of...

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