In yesterday’s post, one of the things I discussed was a study written by McKinsey consultants Brad Brown, Michael Chui, and James Manyika. [“Are you ready for the era of ‘big data?” McKinsey Quarterly, October 2011] In that study, they ask “five big questions about big data” and I promised to discuss those questions in today’s post. The questions concern “important ways big data could change competition: by transforming processes, altering corporate ecosystems, and facilitating innovation.” As I noted yesterday, they don’t claim to have all the answers and acknowledge that “these are still early days for big data, which is evolving as a business concept in tandem with the underlying technologies.” Their first question involves a concept they call “radical transparency.” They write:
“1. What happens in a world of radical transparency, with data widely available? — As information becomes more readily accessible across sectors, it can threaten companies that have relied on proprietary data as a competitive asset. … Cost and pricing data are becoming more accessible across a spectrum of industries. … One big challenge is the fact that the mountains of data many companies are amassing often lurk in departmental ‘silos,’ such as R&D, engineering, manufacturing, or service operations—impeding timely exploitation. Information hoarding within business units also can be a problem: many financial institutions, for example, suffer from their own failure to share data among diverse lines of business, such as financial markets, money management, and lending. Often, that prevents these companies from forming a coherent view of individual customers or understanding links among financial markets.”
Obviously, there is a lot to think about when it comes to radical transparency. Some of the consequences are going to make the business landscape more complex; however, the very big upside of transparency is that it will help break down internal corporate silos. For more on this subject, read my post entitled The Curse of Silo Thinking. Brown and company continue:
“Some manufacturers are attempting to pry open these departmental enclaves: they are integrating data from multiple systems, inviting collaboration among formerly walled-off functional units, and even seeking information from external suppliers and customers to cocreate products. … More integrated data platforms now allow companies and their supply chain partners to collaborate during the design phase—a crucial determinant of final manufacturing costs.”
Collaboration and transparency (or visibility) are both traits that will help define the best supply chains in the future. The next question asked by the McKinsey analysts deals with what I call “what if” exercises. They write:
“2. If you could test all of your decisions, how would that change the way you compete? — Big data ushers in the possibility of a fundamentally different type of decision making. Using controlled experiments, companies can test hypotheses and analyze results to guide investment decisions and operational changes. In effect, experimentation can help managers distinguish causation from mere correlation, thus reducing the variability of outcomes while improving financial and product performance. … Leading retailers … are monitoring the in-store movements of customers, as well as how they interact with products. These retailers combine such rich data feeds with transaction records and conduct experiments to guide choices about which products to carry, where to place them, and how and when to adjust prices. Methods such as these helped one leading retailer to reduce the number of items it stocked by 17 percent, while raising the mix of higher-margin private-label goods—with no loss of market share.”
As RFID technologies become more ubiquitous, even more data will be available and that information should offer further grist for experimentation. The next question involves personalization and customization.
“3. How would your business change if you used big data for widespread, real-time customization? — Customer-facing companies have long used data to segment and target customers. Big data permits a major step beyond what until recently was considered state of the art, by making real-time personalization possible. A next-generation retailer will be able to track the behavior of individual customers from Internet click streams, update their preferences, and model their likely behavior in real time. They will then be able to recognize when customers are nearing a purchase decision and nudge the transaction to completion by bundling preferred products, offered with reward program savings. This real-time targeting, which would also leverage data from the retailer’s multitier membership rewards program, will increase purchases of higher-margin products by its most valuable customers.”
The McKinsey analysts aren’t alone in their belief that personalization and customization are going to change the face of retailing. For more on this topic, read my post entitled Customization and the Supply Chain. One thing is for certain, customization will dramatically increase the complexity of some supply chains. The next question is a bit more controversial (at least the part concerning replacing management).
“4. How can big data augment or even replace management? — Big data expands the operational space for algorithms and machine-mediated analysis. At some manufacturers, for example, algorithms analyze sensor data from production lines, creating self-regulating processes that cut waste, avoid costly (and sometimes dangerous) human interventions, and ultimately lift output. … Products ranging from copiers to jet engines can now generate data streams that track their usage. Manufacturers can analyze the incoming data and, in some cases, automatically remedy software glitches or dispatch service representatives for repairs. Some enterprise computer hardware vendors are gathering and analyzing such data to schedule preemptive repairs before failures disrupt customers’ operations. The data can also be used to implement product changes that prevent future problems or to provide customer use inputs that inform next-generation offerings.”
Improving service is one obvious way that big data analysis can help companies gain customer loyalty. That’s important because many analysts believe that customer loyalty is fading like other industrial age concepts. Improving customer service is not the only way that big data can help a company’s bottom line. The McKinsey analysts report that “one global beverage company integrates daily weather forecast data from an outside partner into its demand and inventory-planning processes. By analyzing three data points—temperatures, rainfall levels, and the number of hours of sunshine on a given day—the company cut its inventory levels while improving its forecasting accuracy by about 5 percent in a key European market.” As they conclude, “The bottom line is improved performance, better risk management, and the ability to unearth insights that would otherwise remain hidden.” Their final question deals with future business models.
“5. Could you create a new business model based on data? — Big data is spawning new categories of companies that embrace information-driven business models. Many of these businesses play intermediary roles in value chains where they find themselves generating valuable ‘exhaust data’ produced by business transactions. One transport company, for example, recognized that in the course of doing business, it was collecting vast amounts of information on global product shipments. Sensing opportunity, it created a unit that sells the data to supplement business and economic forecasts. Another global company learned so much from analyzing its own data as part of a manufacturing turnaround that it decided to create a business to do similar work for other firms. Now the company aggregates shop floor and supply chain data for a number of manufacturing customers and sells software tools to improve their performance. This service business now outperforms the company’s manufacturing one.”
Companies are starting to realize that their databases are tangible assets; but, they have to be careful how to use those assets. When MasterCard started talking to Madison Avenue, privacy advocates smelled blood in the air. The company quickly responded that its talks were preliminary. Nevertheless, it’s inevitable that credit card companies are going to get into the big data analysis business. As noted yesterday, Forrester analysts believe that companies that can help make sense of big data have a bright future. Their McKinsey counterparts agree. Brown and company write:
“Big data also is turbocharging the ranks of data aggregators, which combine and analyze information from multiple sources to generate insights for clients. In health care, for example, a number of new entrants are integrating clinical, payment, public-health, and behavioral data to develop more robust illness profiles that help clients manage costs and improve treatments. And with pricing data proliferating on the Web and elsewhere, entrepreneurs are offering price comparison services that automatically compile information across millions of products. Such comparisons can be a disruptive force from a retailer’s perspective but have created substantial value for consumers. Studies show that those who use the services save an average of 10 percent—a sizable shift in value.”
Cliff Saran reports that a study entitled the “IBM Business Analytics and Optimization for the Intelligent Enterprise” asserts that “one in three business leaders frequently make decisions without the information they need and half don’t have access to the information they need to do their jobs. That has significant competitive implications.” [“What is big data and how can it be used to gain competitive advantage?” Computer Weekly, 1 August 2011] With the dawn of the big data era, those statistics should change significantly. Saran continues:
“According to McKinsey, the use of big data is becoming a key way for leading companies to outperform their peers. ‘We estimate that a retailer embracing big data has the potential to increase its operating margin by more than 60%. We have seen leading retailers such as Tesco use big data to capture market share from local competitors, and many other examples abound in industries such as financial services and insurance, the report says.”
As I’ve pointed out before, big data is not just for big businesses and Saran agrees. He writes:
“While it may seem that huge scientific projects, winning gameshows, and medical research fit in naturally with big data analytics, there is no reason why smaller organizations and those that are perhaps not at the cutting edge of IT cannot benefit. [Rebecca Wettemann, vice-president at Nucleus Research,] believes there is a huge opportunity in big data at smaller companies with cloud computing. ‘One of the really interesting things is the ability for smaller businesses to access applications that are available in the cloud, particularly in marketing and e-commerce,’ she says.”
Hopefully, these dialogues will convince even the most skeptical of individuals that the Big Data Era is not only rapidly approaching but that its first waves have already washed across the corporate shore.