UNDERSTANDING DIGITAL DISRUPTIONS

Digital has taken a central role in forcing fundamental shifts in how business gets presented, revenue is generated, costs are structured, and operations are carried out globally. We could find this in data’s transformative function in healthcare. It is evident in user-generated input and augmented reality and how they revolutionize mapping and navigation. Content development has not been left out with the deployment of algorithms for content curation.  The same changes engulf automation and AI in customer service and influence the use of  3D printing for production and construction.

Digital is causing fundamental transformations in offerings, income sources, expenses, and operations across numerous sectors. Digital disruption spans sectors and organizational activities. Why have digital technologies impacted so many firms and markets? Michael Porter introduced the notion of value chains in his 1985 classic, Competitive Advantage: Creating and Sustaining Superior Performance. A value chain describes the operational steps that a corporation performs to get a product or service to market. An organization is a value chain linked by transaction costs. Logistics management, operations, marketing and sales, and service are primary activities, while infrastructure, people, technology, and procurement are the firm’s secondary activities. A company’s competitive edge is linked to the total of its transaction costs. Companies are established on sustainable competitive advantage, focusing on continual development in efficiency and standardization to minimize transaction costs in specific components. Digital can offer new opportunities for developing competitive advantage, whether the business chooses the cost leadership or the differentiation approach.

As organizations develop, the temptation to add resources and costs and achieve better shareholder returns may cause price hikes. Optimizing products and services justify this necessity. Using Pareto’s principle, a new digitally enabled rival may only give 80% of the value at 20% of the cost. Combining this with a sector-defining improvement in customer experience produces a disruptive threat.

Philip Evans, researcher and Director of the Boston Consulting Group, argues in his TED lecture on ‘How Data Will Transform Business’ that with digitalization, it may become feasible to attain zero marginal cost in some components, meaning there is little or nothing to conserve. Evans contends that when specific elements in the value chain fall dramatically, it can transform the rules of the game for an entire market because it splits up the conjoinment in the industry’s value chain, thus bringing to life new competitive advantages and value chains that did not exist before. This disintegration is even more pronounced if the element that plummeted was that which protected the industry from external competition.

With these changes, vertically integrated, oligopolistic rivalry may transform into horizontal disruptions across industries.  Falling transaction costs undermine value chains’ cohesiveness and allow them to disintegrate.

This idea is similar to Clayton Christensen’s theory of disruption, which states an industry stands on the brink of disruption if its core technology (a critical element in its value chain composition) can be extended or “stretched”.  Christensen references education as a case study. Not many people saw the Teacher as a “technology” that could be disrupted by 2000. Still, with the deployment of Massive Online Open Courses, making available a variety of digital learning materials, and Stanford University making course content available for digital consumption, education is transforming into a completely different future. As a procession of markets succumb to digital disintermediation, where existing mediators are challenged, usurped, replaced, or abolished, the breadth of digital disruption grows.

The Lifecycle of a Technology

The invention of new technology is like surfing; you must catch the wave. Kurzweil Ray Kurzweil, Google’s Head of Engineering, describes the lifecycle of a technological product as an ‘S-curve’. Kurzweil remarked in 2004 that the speed of innovation doubles every decade; therefore, ideas should be directed at the future, not the present, because so many settings change quickly. Therefore, if technologies follow an S-curve (slow, then fast acceptance and development, then plateauing into maturity), you must understand the curves of the lifecycle to perfectly time an innovation. Kurzweil describes seven stages of technological progress.

1. Precursor: the emerging technology’s enabling components are in place (and visionaries may outline its aims or functioning), but it is not yet a reality.
2. Invention requires patience and time.
3. Development: improving an innovation that was likely “ungainly and unworkable.”
4. Maturity is frequently the bulk of a technology’s lifespan. New technology is part of daily existence and feels unreplaceable.
5. False pretenders: emergents attempt to enter the market with claims that they can replace the burgeoning technology. However, they lack some prominent characteristics critical to success resulting in their failure. Failure of newcomers strengthens belief in established technology’s longevity.
6. Obsolescence: Newcomers master the necessary characteristics for succeeding in the old technologies. This development leads to the phasing out of older technologies.
7. Antiquity: the graveyard. Expectedly, nothing else is seen or heard about the old technology.

Kurzweil argues an innovation must go through each step (precursor, invention, development, and maturity) to be successful, which reminds us of Schumpeter’s three-stage model of technological transformation. 1) Invention (ideas); 2) Innovation (commercializing new ideas); 3) Diffusion (scaling or adoption).  Each stage has often overlooked problems, yet we must be good at all three to deploy innovation successfully.

Ray Kurzweil used the S-curve to describe the lifecycle of technology. Still, Charles Handy (in The Empty Raincoat) first told us how the S-curve shows the progression of many successful systems, illustrating the need for significant and regular reinvention and change and how disruption can often happen just when an existing technology is performing its best. Specific curves vary in length, but each begins with trial-and-error learning, fast development, plateauing, and decline.

Overlapping S-curves produced by new technologies or models present difficulty and opportunity (Figure 2.2). Many businesses resist meaningful change until catastrophe or disruption (Point B), typically too late. By then, the organization may spend resources, its competitive position weakened, leadership credibility eroded, and creativity sapped. Starting the shift early at Point A poses problems in terms of transitioning, optimizing the old while constructing the new, and managing distinct and perhaps conflicting business models, modes of working, and cultures concurrently. Change starts here. When you are at Point A, you can look back along the curve and see success and growth, but you can also look forward over the horizon and see the fall to Point B. Looking at the trends may lead you to insights you might not expect. For instance, you may take the information gleaned from data at Point B to discover the right path from Point A to the next curve. Even when things are going well, innovation is key. Two metaphors apply.

The first comes from Dave Snowden, who compares knowing when to focus on the new and stop clinging to the old to knowing when to get in the water while surfing. Your chances of successfully getting on the beach are increased if you move immediately after the tide turns. This should both keep you from being stranded at the beach and help minimise the energy you’ll need to get into the ocean waters.

Clay Christensen describes the sluggish organizational reaction to innovation: When a corporation needs new revenue and earnings, it is too late to invest in new enterprises. Like planting saplings for shade. These trees can not grow quickly enough to provide shade. Growing tall enough trees requires years of care.

Sometimes it is not only companies that make these mistakes but also whole industries. It is one of the most challenging aspects of developing an innovative enterprise. One should remember general advice given to endurance sports performers to deal with this. Eat before you are aware of your hunger, and drink before you feel thirsty.

In Summary: Defining Digital and Applying it to Business.

In this era of digital disruption, it is more crucial than ever to build a shared language for what digital means. It is an excellent place to start a digital transformation.

Digital is defined differently by everyone. Developing a single definition helps the business align around that notion. Few companies do this. Digital is vast, impacting many areas of what we do, and it breaks conventional boundaries between jobs, activities, departments, and categorizations. Having a common understanding offers the basis for a shared vision, a more coordinated strategy, and the groundwork for change.

Many definitions emphasize content, video, mobile, engagement, scalability, and ubiquity, not what digital is. The simplest definition is binary code (ones and zeros)—non-analogue information transfer.

This understanding helps us overcome the concept that digital is a strange, nebulous, ever-changing phenomenon that is hard to comprehend. Instead, it sets it in the context of delivering on or applying everyday needs, wants, and activities. Of course, Digital technologies are changing behaviours and marketplaces, but we should not forget about outstanding companies, products, and brands.

We must consider more than digital’s technical elements to develop a meaningful, informative definition. For example, in companies, there is sometimes a disproportionate focus on the technology itself (new tech for tech’s sake) over all the enablers that surround it, bring it to life, and fully fulfil its capabilities (people, behaviours, processes, skills, culture).

Digital requires more than radically revamping services; it also means transforming our operation.