Overcoming Analog Habits. Part 8: Winning Digital

Did you know that in 1958 (just one year after the creation of the index in its current form), the expected tenure in the index for an S&P 500 company was 61 years and that by 1980, this had dropped by more than half - to 25 years? It’s been declining steadily ever since – now (2016) down to around 15 years - driven by both M&A activity (which was the principal historic driver of “exits”), shifting US macroeconomics and the relentless growth of the “new economy” – essentially the digitization of an increasing amount of both commerce and consumer society.

To keep up with mergers, buyouts and bankruptcies, the index has added (and thus also dropped) an average of 20 companies annually. It's easy to see the difference between today's version and the one that made its debut nearly a half-century earlier. Around 10 years ago it took a market cap of at least $3bn to get into the S&P 500. Today it takes at least $5bn – so you have to grow your market value consistently at around a 5.25 compound annual growth rate to just stay in – never mind moving up the list or avoiding getting displaced by new entrants. That might not seem that hard, but it’s beyond what many companies can consistently deliver. Hence the “churn”: If recent trends persist, over 75% of the current S&P 500 companies will have been dropped and replaced by 2028. So, (a) who will replace them (the raw math says we need to find 375 businesses worth at least $5bn each – potentially adding almost $2 trillion dollars to the economy if they are all actually new businesses that don’t yet exist) and (b) if you’re in the index today, how do you stay in for the next 20 years?

Just as in the natural world, long term survival requires adaptation (or a dominant position in an unassailable niche – and there aren’t that many, if any, of those) and it’s interesting to see how this has played out over the past decades – and what we can learn from the survivors as the evolutionary pressures shift to provide new challenges. 

In general, three common themes seem to be involved:

  •  Running all aspects of business operations effectively, so that the business has (steadily growing) earnings (and thus highly valued equity) to use to invest in…
  • Creating (or acquiring) new businesses which meet new or evolving customer needs, while…
  • Shedding business that once might have been core but now no longer meet company metrics for growth and return on capital, before they become a drag on earnings and valuations (even if they are still “good” businesses).

Pretty obvious, huh? But the second requirement is often at odds (organizationally and culturally) with the first, and the evidence indicates that the third is just plain hard – both in getting the timing right (so you don’t miss value by exiting too early) and then in letting go “emotionally” of past successes while they are still healthy enough to command a good price (so you don’t get left with worthless dregs). 

It’s not surprising, then, that many large and seemingly successful companies slowly fall behind the pace of change of their markets – even companies that were previously the drivers of change. All too often such companies end up continuing on their current course (the course that created their success) rather than managing for the long term evolution of their product lines and business mixes in order to keep pace with the overall changes in the economy. That’s the problem with “decline by erosion” – nothing much changes day by day, but a few years down the road things look very different and catching up with those who started early and got things right is very difficult.

So what would a winning digital strategy have to look like?

One way to build a strategy would be to “think like the market”. Markets as a whole tend to outperform most individual companies (with only a few obvious exceptions that are the major contributors to growth). So companies that mimic market strategies and behaviors should out compete most of their rivals much of the time. Markets grow through aggregate innovation (the creation of new companies that create new value for both existing and customers) and the trading of assets from lower performing managers to higher performing. Companies need to do the same. Just as financial investors are advised not to “fall in love” with assets, so companies should take a hard look at their portfolio of products and brands and ask “could someone else do better with this?” If the answer is “no” keep them and continue to invest for growth. Otherwise sell while there is still value and reinvest the proceeds in something new.

Unfortunately, markets from time to time get out of control for a while (lots of reasons for this, many poorly understood). Companies can’t afford to have this happen. Getting the balance right (visibly in control and able to predict future performance with confidence, but not over controlling, which stifles innovation and creativity) requires a skillful blend of leadership, strategy and operations. To assess how well you are doing in achieving this balance, ask yourself:

  • “Are our business operations as good as they could be, even if they are already the best in class?” If not, the first order of business is to bring current operations up to optimum levels. Undertaking the more challenging tasks of creating new value and trading assets before achieving operational excellence is well established is risky and unlikely to work.
  • “How fast do we have to change to maintain our position within our changing markets?” The pace of change required varies by industry, business line and geography, but you need to be moving at least as fast as the market – a pace increasingly determined by your customers rather than your competitors.
  • “Do all of our control systems work effectively?” “Control” means more than just financial control. It also means operational controls— such as: manufacturing quality and cost; sales effectiveness: and profitability as well as “societal” control, the ethical and legal standards under which business is done. Companies that lose control of these standards rarely come back from the brink of trouble.

As we head towards what’s likely to be a protracted period of global turmoil and intensifying competition, coupled with continuing technological change, the message for senior executives is clear: to maintain control of your business and deliver value to shareholders and customers, you must embrace the continuing creation of new value and actively trade assets without losing control of day to day operations. That’s what winning digital will look like.

Otherwise, sayonara S&P.
 

Overcoming Analog Habits. Part 7: Never mind the competition, can you keep up with your customers?

Ask most business why they are on the road to a digital transformation and they’ll generally cite the need to keep up with the evolution of well-established competitors’ products and services. Logical – what competitors do clearly matters -- but perhaps this focus on competition misses an equally important but different emergent phenomena. I would argue that the greatest challenge to companies today is not to keep up with or ahead of their competitors, it’s keeping up with their own customers – especially if those customers are consumers.

Because individual consumers are transforming to “digital” faster than organizations. If you think each consumer as a tiny business, it’s clear that they’ve already evolved many of their core activities (processes) to be digital. In areas like “procurement” (online shopping), “collaboration” (social networking), “research” (peer recommendations), “finance” (online banking and mobile payments) and “travel” (accommodation or ride sharing) consumers are way ahead of most businesses and the gaps are starting to be embarrassingly visible. Until businesses have evolved and transformed the equivalent processes, they look out of touch with their markets and the consumers that make them up.

Worse, those same customers have much more fluid expectations than before, changing with circumstances and no longer based on traditional boundaries between products, services and even industries. Your customers –consumers and increasingly business buyers – don’t just compare your customer service to that of your competitors. They compare you to the best customer experience they encounter – wherever that might be. The same is true for every aspect of how they interact with you – whether it’s your web site, your mobile app, your loyalty program, your brand promise – potentially even your stance on ethics, sustainability and social responsibility.

So if your customers are setting the pace that you must compete with, how can you keep up with them? You’ll have to start thinking and behaving like them, starting with the elimination of tradeoffs in cost availability and quality.

It used to be said that you could pick any two features from “cheap, good, or fast.” Today’s customer doesn’t think like that. If they can get anything that’s cheap and good and fast somewhere (and generally they can), they’ll expect everything to be that way everywhere – or they’ll go to wherever they can get it that way. As executives, we are accustomed to thinking of business strategy being about making tough decisions between competing objectives within constraints of resources time and money. But if we must start to think more like our customers., we need to focus on how to eliminate tradeoffs not on how to make them. That’s a whole different set of skills.

Here are some of the tradeoffs that are going to have to change if you hope to keep up with your customers:

  • You need to be able to act big and small at the same time: It’s easy to be fast, agile and creative if you’re small, but you’ll need the reach, scale and presence associated with being big to serve a large fluid customer constituency
  • You need to be able to manage both complex global systems and simple, engaging customer experiences: To the customer you’ll need to look like you’re engaging in a one-to-one relationship, but to do so is immensely complex in a digital world awash with information and regulation. Your systems will have to both mask this complexity and adapt quickly as the rules change
  • You need to be present everywhere your customer might be without becoming impersonal: Deliver a consistent and satisfying interaction experience anywhere, at any time through any channel of the customer’s choosing, always in the correct context, always relevant and engaging.

Customers will no longer accept the feeling that you’re controlling them – forcing them to do what’s best for your business, rather than what’s best for them. They want their relationship with you to be based on reciprocity and transparency – to feel authentic rather than forced. If you want to keep up with your customer, you can’t be focused on what you want them to do: you’ll have to learn to help them do what they want, when, where and how they want. That means every aspect of customer engagement has to change fundamentally. You’ll have to be as agile as they are and as responsive as they expect if you are going to win and keep their business.

This is going to mean rethinking and probably reinventing a lot of established customer relationship disciplines and it’s going to be a significant shift in mindset and skill set to switch from tracking what your competitors are doing to understanding what your customers expect from you.

Creating sustainable advantage will be more elusive than ever. Customer-driven journeys will have to span constantly morphing interactions and focus on their intent, not yours, creating and maintaining much more complex relationships. The most successful companies will leverage these complex, dynamic, information rich interactions to anticipate, rather than just respond to, their customers’ needs. It’s time to stop thinking about just keeping up with your competitors, and start thinking about how to get ahead of your customers.

 

Overcoming Analog Habits. Part 6: Moving beyond the cultural status quo

In the previous five posts on digital transformation (DX) I’ve looked at some of the significant challenges for enterprise IT to overcome, but these challenges may be less important than what I see as the real impediment to going digital – virtually all large enterprises have become efficiency-driven machine bureaucracies where you don’t get rewarded for taking risks, trying new things or for being different. Reward and recognition systems get in the way of the changes and innovations that are needed to rapidly move the digital transformation forward. It doesn’t matter what the senior executives and managers say – what matters is what they do – and what they generally do is try to apply familiar machine bureaucracy patterns to a dynamic, fluid, evolving environment. 

It’s as if a failure you understand is better than a success that you don’t.

What’s needed (somehow) is a way to become a smart experimenter; to perpetually try out a range of new digitally-focused ideas (preferably with credible value propositions attached – but be prepared to take a flyer now and again) in partnership with your employees, suppliers and customers; select those that work; and then adopt and scale them quickly. Think big; start small; learn fast.

You can try to do this in-house (which has turned out to be very tough for most large businesses) or via the market, which has often been easier. But successes generally cost more to buy than build and you need a way to track what’s being tried and identify what’s succeeding. However, if you can’t successfully build internally, buying others who have managed to do so may be your only option – if you understand what made them successful and can incorporate that success into your business without diluting or destroying it. 

Whatever route you choose, you’ll still need to become very good at integrating the stream of new ideas into a consistent operational framework, so that they’re not just new, they’re operationally efficient right from the start and potentially able to make a profit contribution as early as possible. If the business services framework that every business idea needs is already in place and ready to go, you’ll be in the market faster and able to evaluate success quickly. Just by itself that’s a huge advantage.

Getting to digital is a journey, already decades long and probably never completely over – there’s no limit yet to the potential for a fully digital business to innovate and grow. It’s not going to be an easy or even an obvious transformation, but it’s going to happen to everyone, everywhere to some degree sooner or later. So you do need a strategy, but not one that assumes that anyone knows what the outcome will finally look like. Better get ready.

How’s your evolution to digital going?

 

Overcoming Analog Habits. Part 5: DX:IT Transforming enterprise IT for the digital world

For most of the past (pick a number) decades, corporate IT leaders have been forced into a balancing act. On the one hand, their business colleagues, increasingly dependent on automation to improve productivity, have insisted on stable, reliable, always available technology. On the other hand, those same colleagues want fast response to changing business conditions, new product ideas and competition. All within strict financial constraints, a constantly evolving technology landscape, new vendor strategies and a shortage of skilled technology talent. This has always been a tough balance to achieve and in most cases, corporate information systems haven’t kept up with the rapid evolution of hardware and software capabilities and, as a result, often can’t readily adapt to the new requirements of a digital world. 

The business response4 has all too often been to look outside – to outsourcing (until it became apparent that most outsources were no more flexible and efficient than in-house IT, and often no cheaper and less reliable); to software as a service, with its network reliability challenges and required but seldom anticipated investments; to “cloud” computing, with its security, availability and manageability challenges.  By now we should have learned that getting enterprise IT right in any circumstances isn’t easy, but in the digital world, it’s essential. So, if you need the right capabilities and decide to keep them in-house, what’s needed?

First, let’s admit that an instant wholesale makeover of enterprise IT isn’t going to happen. There’s too much legacy; too much need for stability and availability; too much potential for an adverse impact on the balance sheet. The disruption resulting from any large scale change over a short period of time would be disastrous for virtually any business. 

So the transformation will have to be progressive and carefully executed. At the same time, it can’t take too long, or you’ll be left so far behind that catching up may be impossible. That implies that there must be (a) priorities that you focus on to get started; (b) a road map to keep up the momentum needed to maintain progress and (c) a plan to sunset the technologies and skills that won’t be what you need in the digital future. The specific priorities will depend on where you are today, but in general, here’s what I expect you’ll need to focus on:

  •  Develop a “FAST IT” mindset and set of capabilities: It’s important to recognize that application delivery speed drives business success and speed requires a new level of agility. You’re going to need some flavor of Agile development process and be willing to adopt DevOps approaches, because it’s no good developing things quickly if you can’t get them into production just as fast. You’ll also need rapid scalability in capacity (both up and down) to take advantage of the ideas that succeed and to match actual variable business demand. That’s going to require a lot of automated management capabilities based on a very granular level of operational performance monitoring. The required tool chain will take time to assemble and learn to use well, but you’ll absolutely need it to meet or exceed your internal and external customers’ expectations and experience for availability and ease of use. And while you’re at it, don’t forget to encourage and reward continuous improvement and innovation ideas from both your staff d your customers.
  •  Adopt a “Bi-Model” operational approach: Balancing responsiveness and agility with reliability and high (probably continuous) availability requires a set of standardized, simplified, automated platforms and processes. Sure, you’ll have plans to sunset most of your legacy environments, but that’s no excuse for not becoming as efficient as possible in supporting them until they’re retired. You should look at implementing on-demand provisioning and dynamic capacity management capabilities – you’ll need them for emerging platforms and they can be a big help with legacy platforms too. Consider building a scalable “back office” platform for the smart products and services you’re introducing, including support for emerging ideas like IoT, and include capacity for big data and analytics. Aim to sunset platforms that can’t meet the needs of the digital enterprise within 3 years
  • Support Mobility: Digital omni channel requires you to provide support for secure access from and secure delivery to any device, anywhere, anytime, so build this in form the beginning for every new idea. Embrace Interoperability inside and outside the enterprise and adopt an “API Economy” architecture and appropriate data sharing strategies across all platforms. Create and evolve a “data blending capability” to leverage internal and external data sources and establish the governance that you’ll need to make this work seamlessly and securely.
  • Enhance Security: You’ll need an “open but secure” security architecture – you’ll have a lot more active connections to manage – that includes appropriate segmentation of assets and defense in depth. You’ll also need to avoid “weak links” in your ecosystem and have a way to verify that your partners’ security doesn’t leave you vulnerable.

See why you need priorities and a road map? There’s so much here that must eventually change and evolve that it can paralyze an organization that tries to do it all at once. Just as the business will become digital incrementally, so must enterprise It change incrementally to get ready the capabilities in place that will be needed, free up resources to work on new things and get the basics right. It won’t be easy, but it will be necessary.

Overcoming Analog Habits. Part 4: Creating a viable business model

Making things “smart” by adding sensors, data storage and network connections opens up a multitude of possibilities and is core to the creation of a digital business. However, many of the things that are technically possible (and often popular with enthusiasts) have little or no economic justification and hence don’t necessarily represent a business opportunity on their own. Just because you can do something doesn’t make it a good idea.

We’ve seen this play out before, most recently with Radio Frequency Identification (RFID) – adding mostly passive data storage to items so that they can be efficiently tracked throughout the supply chain by a network of scanners installed in manufacturing plants, warehouses, distribution centers, trucks and retailers. Being able to track and positively identify items clearly helps combat forgery, counterfeiting, theft and lost or misdirected packages and there was a strong (and valid) business case to do this for high vale or safety critical items.

However, many enthusiasts tried to extend the ideas to “everything”, using an argument that “optimizations” would deliver enough benefits to pay for the added costs of RFID tags and infrastructure. A detailed study and modelling exercise undertaken by the Grocery Manufacturers Association (GMA) demonstrated that even if the tags were free to make and attach, the costs of the rest of the infrastructure (readers, data management and storage and analytics processing) exceeded any possible benefits from reduced spoilage, wastage and “shrink”.

It took a while form this reality to sink in and a lot of time and effort was wasted before the value of RFID could be focused on the use cases where it made sense. The same thing seems to be happening with some areas of digital transformation – especially those areas associated with the “Internet of things” (IoT), often cited as a primary driver of DX. While there are clear business cases for many IoT applications in the Industrial and some commercial sectors of the economy, it’s less clear that these justifications hold up for the potentially much larger consumer IoT opportunity. It costs money to make things smart and connected and then to collect, analyze and store the data those things generate. Unless we can reduce operational costs for products and services as a result, we’re going to need someone willing to pay for what we can do. It might be possible to charge for “convenience” – anticipating device failures or preventing an empty pantry, but it’s by no means certain that enough people will place enough value on the capability to build a business on it, let alone create a competitive marketplace. RFID still (over a decade later) isn’t cost competitive for low value items with thin profit margins. IoT probably won’t be much better – at least for a while.

“Freemium” market strategies might help in some cases, but you can’t pay for everything with advertising – even good engaging advertising – and if you can’t Freemium means you have to convert a reasonable number of “free” customers to “paid”. Digital business models need to be able to model these assumptions and test them for reasonableness and stability: can they ever work under even the most optimistic circumstances and even if the can, will they last long enough to be worth investing in?

Although we have a tendency to believe the technology enablement means “this time it’s different”, it very rarely is. Economics 2.0 seems to elude us every time. Don’t bet on it this time either. There’s plenty of DX opportunities that do have viable business models attached. Let’s go after those first.

Overcoming Analog Habits. Part 3: The need for trust - Getting comfortable with porous boundaries

Going digital effectively blurs the edges of the business you are supposed to manage and requires a broad focus on cooperation and collaboration as much as it does on strategic direction and operational control. In an ideal digital value chain, information is shared amongst all contributors so that each can actively contribute to an overall optimization strategy in the specific context of each relationship in which they participate. There’s significant upside to getting this right, but sharing also comes with potential risks. What happens if your value chain partners get acquired by your competitors, or byb their competitors that serve yours? Who’s responsible for things like data integrity and end-to-end information security? In the old analog world, it was possible to identify clear “boundaries” that defined the edge of each participant’s roles and responsibilities. In a fully integrated digital world, that’s too inefficient – duplicating some processes and misaligning others – even where it’s still possible.

Generating strong trust in the digital world is therefore essential. There can be no weak links in the technology, human or process chains that tie the operational value chain together. There will have to be standards that everyone actively buys into and implements completely and correctly. There will have to be processes that both effectively onboard relationships with new partners and sever relationships with old partners. There will have to be policies that determine what can be retained after relationships are severed and what can be shared immediately when relationships are first created. And there will have to be agreements on the many elements of operational and strategic governance. All these without slowing down the ability to respond to the pace of change.

It’s no longer sufficient to rely just on contracts and service level agreements, even if these may still be needed to memorialize the scope and commitments of the value chain relationships. We will need to create trusted connections based on reputation, mutual transparency and collaboration. That’s going to be challenging for the many companies who participate in multiple value chains and must securely segregate information and activity visibility to maintain confidentiality and trust with their many business partners.

There’s going to have to be a lot of focus on good governance, especially good data governance. Data sits at the heart of virtually everything digital and if you don’t know where all that data came from, how reliable and current it is, what it’s there for, who owns it and who has permission to use it for what purposes, bad things can happen. It’s also likely that when you start looking at your data in detail, you’re going to find inconsistencies and gaps. You’ll need policies on how to deal with these issues – and they’ll need to align with your value chain partners’ policies and practices.  As powerful as our data management tools have become, they can’t solve all of these issues without human effort. Given that this effort is generally going to be significant – not just for shared master data, but eventually for all data – the time to get started was some way in the past. When everyone has to depend on a common set of information, you can’t afford to tolerate inconsistency – and because inconsistency is inevitable in many circumstances, processes and resolution practices that do tolerate it are essential and will need to be developed.

Waiting to get them in place won’t make it any easier.

Overcoming Analog Habits. Part 2: Moving beyond intuition in decision making

Although they shouldn’t be, information based decisions can be harder to accept than intuition or “experience” driven decisions (another of the analog habits that are hard for us to break).

In the fairly recent past, I worked as a part of the leadership team at a company that was built and run almost entirely on the intuition and instincts of the small group of founders. There was plenty of raw data and a good deal of relevant information around too, but when it came to the critical decisions around strategy, key customer relationships and managing enterprise risk, what the information told us generally took second place to the gut feelings of the core of senior leadership. Given that this approach had built a highly profitable public Fortune 1000 company from scratch in less than a decade, it was hard to argue with the approach – at least for as long as the founders were around, active and making effective decisions.

However, as the business continued to grow it was clearly going to be harder, and eventually impossible, for every key decision to be vetted by the core set of “intuitions” that had driven previous success. It was also increasingly difficult to keep regulators and the market (in the form of financial and industry analysts) happy that the business was being run on a sound footing. Even some of the largest customers began to question the seemingly ad hoc approach to using comprehensive, accurate and up to date business information to manage customer relationships.

Things came to a head when it was time for some of the founders to step aside. New management wanted information-based decisions, not gut feelings – which triggered a cultural upheaval in large part because the founders had generally hired people who operated pretty much the same way they did – on intuition and instinct. Even when they trusted the data, they often preferred not to use it.

As it turns out, I’d seen situations like this before.

Humans generally have good intuition about things that are similar to what they encounter every day and are able to make “instinctive” decisions that are generally correct. They have poor intuition about things that are unfamiliar and outside of their everyday experience and very poor intuition about things that are totally alien to everyone – things outside of all human experience. This is especially true when dealing with scale effects (very large or very small numbers for example), complexity or non-linear processes (such a riots or bank runs or “flash mobs”).

Even in business there have been examples where information guided intuition in meaningful ways. The “Information based strategy” (IBS) approach adopted by the Capital One Financial founders in the late 1980s is one of the best known. Other information (or at least data) based strategic approaches were adopted by companies such as GE (under Jack Welch) and it can be argued that many of the data-focused management tools of the past 50 years have been attempts to take the intuition and instinct out of routine business management processes and replace them with “facts”.

Of course, information-based approaches depend on access to comprehensive, accurate and up to date information that is actually relevant to the decisions being made. Both too little and too much information often derails these approaches, forcing executives and managers back to using intuition and instincts that may not have been well honed for the task.

So what should we be doing? What place does intuition play in a world awash in “big data” and ever more powerful “analytics” tools?

As is often the case, the best answer seems to be in striking an appropriate (if difficult and dynamic) balance. Just as our intuition is less than perfect, so in general is our information less than complete. We should certainly ask “what does the data tell us?” before forming a hypothesis or making a decision, but there will be instances where what the data tells us is ambiguous or confusing. That’s where reasoned judgement, experience and if necessary intuition step in. Using information (remember that it needs to be as complete as possible, accurate and up to date – none of which come free) to enhance and support our intuition should be the objective of every modern business.

The old adage that “you are entitled to your own opinion but not your own facts” applies even today. But with the right facts to back you up, your opinions are likely to be much more valuable.

Overcoming Analog Habits. Part 1: Learning to cope with exponential information growth

One of the things that makes Digital Transformation (DX) hard stems from the fact that we pretty much all grew up in a largely analog world and hence have a lot of “analog habits” that are hard to break, especially if we are “experienced” senior and middle managers who got that way by being good at managing in an analog world. It takes a while to realize that digital assets are qualitatively and quantitatively different from analog assets and therefore require new and unfamiliar management approaches to their creation, management, protection, ownership and use.

Effectively collecting, validating, managing, protecting and using all that digital data is technically challenging and expensive. Before the invention of the printing press in the early part of the 15th Century, “information” transfer between people and between generations was limited to what was believed to be important and needed to be remembered. Hand copying documents was slow and laborious – and hence both limited in volume and expensive. Errors occurred in copying. Ideas were lost – or limited to the few people who could afford to create and maintain libraries.

Increasingly available and relatively low cost printing changed all that – generally for the good. But widespread literacy was not an overnight event; reading and writing ability remained a source of competitive advantage; “truth” was no easier to verify in print than when hand written; and “spam” was probably invented at about the same time as the printing press.

Over the succeeding six centuries we have seen an explosion in the quantity (if not the quality) of information that’s being created, collected, stored, retrieved, analyzed and fed back into the processes of our daily lives. Now we create the same amount of data every two years as we had created up until the start of any given period – a doubling every 24 months. Pretty much no one understands the impact of that kind of exponential growth, because it’s outside our experience. Exponential growth seldom occurs in nature – and when it does occur, it seldom has a good outcome.

So digital transformation requires us to get comfortable (or at least competent at) dealing with very large volumes and varieties of data moving at ever higher velocities. In the digital world there will always be too much data to review and too little time to react. We need an effective and efficient tool chain to manage all this. The tools aren’t all there yet, but there are more than enough to get started with – and they’re getting better all the time. Availability of trained and experienced users is an issue, but the basics aren’t that hard to learn and a lot of existing skills in data management fields can be repurposed and expanded to handle “big data”. 

It might take a while to build up the resources you need, but it won’t happen until you get started and not getting started pretty much guarantees that you’ll get out competed by those who do.

The Challenges of Going Digital

I have been reading a lot lately about the evolution (revolution) of digital business. I‘ve even had several clients ask me what they should be doing to “become digital”, what a “digital strategy” should look like and how they should manage this transformation. Now, the steady digitation of life and business has been going on for quite some time (certainly since the advent of the consumer Internet and arguably long before that) and the replacement of analog items (and related information) with a digital version has been pretty visible as mobile devices have proliferated. More people still check in for a flight with a paper boarding pass than use the electronic version on their phone, but the trend is clear.

In fact, this continuing shift to “digital” mirrors in many ways the shift to, first, online commerce and second mobility.

Online commerce arguably really started with Amazon’s launch in 1997 and is still underway – with a ways to go to become even a majority of readily addressable commercial activity. Low cost PC deployments (at work and at home) and broadband Internet were the enablers, along with there actually being something to buy, a way to (safely) pay and an effective delivery system. The
“surprise” that Amazon’s success depended on was a willingness of consumers to buy things they had never seen – an extension of the well-established process of “catalog” shopping with radically different economics. Nearly 20 years later, these are still the primary elements driving online commerce, but mobility is changing the landscape.

The “year of mobile” was proclaimed annually for most of a decade as 2G and 3G networks were built out; limited, low bandwidth data capabilities were added to early cellphones and simple email and text services were deployed by carriers, juggling the desire for additional service revenues with the scarcity of available spectrum where users wanted it most (in and around major cities). Then came the iPhone (2007), Android (2008), 4G (2010 in the US) LTE (2011 in the US, somewhat earlier in Europe) data services (which are much more spectrum and infrastructure capacity efficient) and the result was an explosion in consumer and business demand for mobile access to data of all kinds. It wasn’t really any one thing that triggered this – but the confluence of enhanced device capability, attractive and easy to use user interface software, spectrum growth, improved platform efficiency and carrier competition combined to trigger a rapid change in consumer behavior. LTE-A (2015 in the US) and 5G (probably around 2018) are likely to continue the mobility evolution.

So it is with going “digital”. “Being Digital” – Nicholas Negroponte’s excellent summary of how we got to the start of the digital era was published in January 1995 and while not focused on predictions, did point out many of the trends that have shaped the ensuing decades. Consumer products started setting the standard for user expectations and the environment and tools used in the workplace were forced to evolve in response. People wanted that same ease of use and richness of function they could get at home while they were at work. The start of “consumerization” would inevitably change many things beyond the consumer and continues to do so.

Large scale automation of core business processes really got started in the “reengineering” wave of the mid 1990s, powered by the need for significant employee productivity gains, an “always on” business operating capability, the need to recoup the cost of rapidly evolving technology and the globalization of commerce. Initially an internally focused (and expensive and disruptive) effort, the parallel growth of the Internet, online commerce, self-service models and globally integrated supply chains soon forced an inter- rather than just intra-corporate perspective. A direct byproduct of process automation was the accumulation of very granular data about every aspect of business operations and customer activity, driving further product and service optimization opportunities. The more you know about your customers, your products and your people, the better you can serve those customers, evolve those products and engage with those people.

Then came social media and the real digital data flood started. Although social media goes back a long way (to before the consumer Internet) the launch of LinkedIn in 2003 and Facebook (to the public) in 2006 opened up the digital world to hundreds of millions (now billions) of “ordinary” people – who are also consumers, investors, commentators and employees.

So going digital is not just about doing any one particular thing differently – it’s about doing many things (in some cases everything) differently, which is always hard. But today, a business that isn’t going digital risks analog isolation in a digital universe. No one wants that.

You’d think that all of the hundreds of billions spent on technology, process automation, connectivity and software over the past 30 or so years would have already moved everyone to the evolving digital world, but it hasn’t – that’s why we are still talking about it and about what it means. An evolution that seems like it should be straightforward, hasn’t been and still isn’t. Here’s some reasons why:

We have “analog habits” that are hard to break, especially at senior and middle management levels. Digital assets are qualitatively and quantitatively different from analog assets and need new and unfamiliar management approaches to their creation, management, protection, ownership and use

  • Effectively collecting, managing, protecting and using all that digital data is technically challenging and expensive
  • Information based decisions can be harder to accept than intuition or “experience” driven decisions (more habits that are hard to break)
  • Going digital effectively blurs the edges of the business you are supposed to manage and requires cooperation and collaboration as much as it does direction and control
  • Many of the things that are technically possible (and often popular) have little or no economic justification
  • Corporate information systems haven’t kept up with the rapid evolution of hardware and software capabilities and can’t easily adapt to new requirements of a digital world

These are significant challenges to overcome, but they are less important than what I see as the real impediment to going digital – virtually all large enterprises have become efficiency-driven machine bureaucracies where you don’t get rewarded for taking risks, trying new things or by being different. Reward and recognition systems get in the way of the changes and innovations that are needed to rapidly move digital forward. It doesn’t matter what the executives and managers say – what matters is what they do – and what they generally do is try to apply familiar machine bureaucracy patterns to a dynamic, fluid, evolving environment. It’s as if a failure you understand is better than a success that you don’t.

What’s needed (somehow) is a way to become a smart experimenter; to perpetually try out a range of new digitally-focused ideas (preferably with credible value propositions attached – but be prepared to take a flyer now and again) in partnership with your employees, suppliers and customers; select those that work; and then adopt and scale them quickly. Think big; start small; learn fast.

You can try to do this in-house (which has turned out to be very tough for most large businesses) or via the market, which has often been easier, but successes generally cost more to buy than build and you need a way to track what’s being tried and identify what’s succeeding. However, if you can’t successfully build internally, buying others who have managed to do so may be your only option.

And whatever route you choose, you’ll still need to be good at integrating the new into a consistent framework. Getting to digital is a journey, already decades long and probably never completely over. But it’s going to happen to everyone, everywhere to some degree sooner or later. Better get ready. So you do need a strategy, but not one that assumes that anyone knows what the outcome will finally look like.

How’s your evolution to digital going?