Using Big Data To Defeat Market Insurgents

How incumbents can use their data in times of disruption


The last 20 years have seen disruption on an unprecedented scale. Movie and music streaming rendered DVD rental and CDs obsolete, tiny personal computers replaced the minicomputer, web retailers have disrupted brick-and-mortar operations, and digital photography made film irrelevant. This has left a trail of fallen giants, with Wang Laboratories, Woolworths, Tower Records, Blockbusters, and Kodak among the many to fall by the wayside.

The last few years have seen the level of disruption intensify even further, driven by the democratization of technology, a massive influx of investment from venture capital firms, and a growing culture - among millennials in particular - towards entrepreneurship.

Organizations seem to be hyper-aware of the problem. In a recent Accenture Strategy survey, 58% of CFOs said they believe their industries are set for disruption, 24% that disruption will destroy their company, and 41% that more than half of their competitors will cease to exist as a result. Such high numbers imply a certain degree of paranoia, likely caused by the publicity around the more significant collapses. In most industries, disruption is usually a fairly slow process and rarely happens at the speed and to the degree we saw with, say, Blockbusters. For example, when the first low-cost airline, Southwest Airlines, was established in 1967, many predicted it would herald a new dawn in the industry, yet legacy carriers still fly millions across the world every year. They simply adapted. Some cut prices, some emphasized the greater quality service they provide, and many others have achieved similar feats.

However, paranoia is not necessarily a bad thing. It is best to be prepared, and many incumbents have more than sufficient resources to stay ahead of the curve and exploit new trends. They have brand loyalty, a global distribution network, and institutional know-how far in excess of their startup competitors, no matter how advanced their technology. You could argue, reasonably, that Blockbuster and Kodak had the same resources, but their failure to adapt is unusual, as shown by the simple fact that they are still so often cited as examples.

The key to successfully defending against disruption is simple. You have to stay ahead of the competition, both new and old. And essential to this is data and analytics.

The wealth of data incumbents have to hand is one of the primary advantages they hold over their rivals, and they can leverage it in a number of ways. In the late 1970s, Dick Foster, then a management consultant at McKinsey, argued that well-run market leaders often failed when the dominant technology in a market shifted abruptly, rendering all the expertise that they had built up irrelevant. Foster labelled these moments ‘technological discontinuities’. Data, however, can always be made relevant. And it can help companies stay ahead of technological shifts. In his 1986 book, Innovation: The Attacker’s Advantage, Foster argued that the first step an incumbent can take is simply being aware of the possibility of a technological shift. Data analytics gives an organization a degree of hyperawareness that enables it to detect and monitor both internal and external factors that are causing changes in its business environment. Companies can use data to anticipate which non-traditional competitors (startups, incumbents from other industries) could threaten their market position. They can gain insight into future and emerging trends by applying machine learning analysis to the unstructured data on social media to understand what consumers are saying about both their offerings and those of their rivals, and any potential shift in their desires. They can see when their customers are dissatisfied en masse and the cause, and often what the solution is likely to be to resolve their complaint. Analysis of customer sentiment allows them to pinpoint what it is the customer truly values about their products so they can adapt technology that improves them while retaining their core selling point. Organizations can also collect massive amounts of external data that could indicate which way the market will shift next, or highlight an opportunity that could be exploited. For example, competitors’ activities, macroeconomic trends, and weather patterns. Essentially, with data companies put them in a position where they are less likely to be taken by surprise.

Not only are they less likely to be taken by surprise, they can also react far quicker. It provides decision makers with more information where and when it is needed, enabling faster execution and better agility. Predictive analytics can also give an indication of how likely their attempts are going to be, and assess the likelihood of success around strategies and new products that they may adopt to deal with disruptors.

One example of a large incumbent that has successfully used data to operate in a fast-evolving space is Royal Mail. Royal Mail has been around for roughly 500 years, but as email has replaced letters and demand for same day delivery of packages increased, they have had to adapt quickly, especially given the number of competitors now moving it. Aki Matsushima, formerly a Data Scientist at the Royal Mail and now Lead Data Scientist at Direct Line Group, told us that, ‘People are sending fewer letters and there is fierce competition in the parcels market. We are trying to take advantage of Data Science wherever we can to improve our existing operations and to develop new services using our unique data.’ Royal Mail’s 160,000 employees deliver billions of letters and parcels that provide a host of data touchpoints. The director of the Technology Data Group at Royal Mail, Thomas Lee-Warren, told Computerworld UK that they ‘are about to go up to running in the region of a hundred terabytes, across nine nodes,’ and to analyze this they require a data insight team of 15 permanent members, which can go into the hundreds when third-parties are involved.

Such resources are beyond the realms of possibility for the large majority of disruptors. But this does not mean that incumbents should rest on their laurels. What startups do is use the data they have better. Most are built to be data-driven from their inception and they have the processes, talent, and technology in place to put them in the best position to analyze data and convert it into action as quickly as possible. This is also partly a result of their size, but large companies need to learn from them and adopt their tactics. They need to ditch the old-school approaches to designing change. This means no more cumbersome annual strategy meetings, no more yearly forecasting, no more time wasted on outdated company structures that stifle innovation, silo data, and generally get in the way. The degree to which disruption takes place may often be overstated, but any company that takes their position for granted is unlikely to last.


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