The Business Case for the Digital Makeover

Big Data, IoT, Analytics open new vistas for customer experience and operational jumpstart


Arun Shukla

You may never taste the data bits that are a key ingredient in Domino’s Pizza. They are baked into the company, changing over time as hungry customers moved their ordering from landline phone to Web to cellphone to mobile app. These days, 60% of pizza orders come from mobile devices, apps, Facebook—anywhere but a home phone.

Domino’s “Pizza Tracker” engages the customer in a novel way by providing real-time updates from order to delivery. That’s pretty interactive for dough, cheese, toppings and heat. It’s a new approach to the basic job of making food. 

Other examples are drawn from the auto repair shop sending you a video and email of your vehicle while it’s being fixed. Or home delivery of custom, made-to-measure clothing that is displacing mall-based retail stores. There are countless reinventions going on that have potential to alter our daily experiences. 

Businesses are racing to connect physical dots to virtual dots to capitalize on both technology and marketing for gathering data, getting closer to the end user, in order to drive meaningful digital change.

What is unlikely to change are the basic rules of business case monetization, robust application of technology, and managing the human side of change. Rules that applied for the industrial economy are just as relevant for the digital economy.

An important starting point is finding value for buyer and seller, often called the “Use Case.” Business teams spend crucial hours on use cases, for instance, and some have suboptimal outcomes. Consider these examples:

  • A maker of pumps for oil/gas production proposed adding sensors to measure speed, temperature, and noise. Customers of this “smart” pump would be able to interpret data to anticipate failure, proactively make predictive replace/repair decisions and increase productivity. But a downturn in the oil industry meant excessive underutilized capacity, which in turn made it cost prohibitive to upgrade the fleet and resulted in poor adoption. 
  • Implantable cardiac devices with wireless functionality to monitor and control patient heart functions and prevent heart attacks were found to have security vulnerabilities that could allow a hacker to access a device. Once implanted, a hacker could deplete the battery or administer incorrect pacing or shocks. The US Food and Drug Administration decided the technology was not secure enough for a critical life support device.

Technology does have a dark side, and the Internet of Things (IOT) is no exception. When Caller ID was a new technology in the 1990s, it allowed companies to exclude poor communities or high-crime areas. Remote networked telematics brought roadside assistance to vehicles via OnStar—but also used it to disable ignitions on vehicles when buyers fell behind on payments.

Another key consideration is the “right” data used the “right” way, with appropriate controls. Automobile insurance and rental car driving patterns might sound like a good place to capture data on driver behavior, use and maintenance. Progressive Insurance, for example, offers discounts to clients volunteering to share this data, yet the concept to adjust rental car prices for different drivers might be too intrusive if even anonymous data were used to discriminate against higher-risk renters.

IOT envisions capturing and interpreting data and pushing out predictive adjustments. However, there are risks associated with overstepping into privacy or customer tracking. Striking the right balance of enhancing customer experience in a secure manner while making financial sense is critical. 

Consider this framework for getting it right:

People, Processes and Technology

One useful exercise is a simple bar graph to evaluate the merits of any digital initiative. List the three primary areas of impact People, Processes and Technology on the x-axis. Then indicate the potential degree of change for each specific digital initiative on the y-axis as Low, Medium or High.

If all three areas are likely to produce a high degree of change, consider whether it’s too disruptive, with potential for a positive business breakthrough, and discuss possible risks. Conversely, a low degree of change may tell you that digital initiative benefits are not worth the effort. Look to quantify positive/negative consequences and any dependencies that rely on changes within the ecosystem of customers, partners, suppliers, repair or after-sale issues.

And what are your competitors doing? Is yours a copycat move, an industry standard practice or a true innovation?

Further, data streams from IoT devices are commodities and are unlikely to be sustainable sources of revenue. The monetization of these data streams will come from contextualizing the vision by building use cases that match requirements with the list of objectives for events, processes and decisions and including the ecosystem of various stakeholders in a secure manner that transparently communicates to the end user the risk and benefits of sacrificing privacy. 

“Pizza Tracker” clearly communicates changes and benefit. Just because a product sold well yesterday is no guarantee it will sell again tomorrow with an IOT sticker. But Domino’s stock is up 5000% since 2008, according to the Los Angeles Times. That’s a good answer to the question, “What’s in it for me?”


Arun Shukla is a managing director of Berkeley Research Group, based in Atlanta. He leads BRG’s Corporate Finance Strategy & Operations team.