Creating Customer Value Using Analytics

Data wrapping occurs when companies combine a product or service with analytics with the intention of increasing the customer value proposition. One of three data monetization approaches,[foot]Barbara H. Wixom and Jeanne W. Ross, “How to Monetize Your Data,” MIT Sloan Management Review, Volume 58, Number 3, Spring 2017, pp. 10 –13, http://sloanreview.mit.edu/article/how-to-monetize-your-data/.[/foot] data wrapping can be used to reinforce, streamline, or enrich the usage or experience of an offering. Consider how Amazon.com customizes online shopping so that customers can more quickly navigate a sea of product choices; or how heavy equipment manufacturers can predict and then prevent parts failures. Data wrapping adds customer value when it uses sophisticated analytics to solve problems that are meaningful to customers. This requires that companies recognize customer needs, shape analytics into solutions, and seamlessly help customers solve problems. 

DATA WRAPPING USE CASES ALONG THE CUSTOMER JOURNEY 

MIT CISR research has identified hundreds of data wrapping use cases[foot]The research is based on three data monetization studies: “Winning with the Internet of Things” (2016), “Data Wrapping” (2017), and “Datatization as the Next Frontier of Servitization” (2017). The studies examined surveys (combined N=240) and interviews (combined N=43) from business and IT managers, and a total of thirty-two publicly available use cases.[/foot] that fall along the customer journey. Companies can apply data wrapping to any customer touchpoint (e.g., purchase, usage, service), and typically choose to wrap in areas where customers most need help or the company can create the most value. Along the customer journey, data wrapping use cases can contribute data, insight, or action to a solution (see figure 1). 

• Data: Some use cases arm customers with data—in the form of reports, dashboards, visualizations, or even APIs—that the customers can then employ in meaningful ways. For example, one B2B financial company offers its institutional clients API access to their near real-time transactions, from which the clients can draw data for generating reports. Many machine manufacturers offer their customers access via online portals or email reports to machinery data with which the customers can better understand machine usage as they manage operations. 
• Insights: Use cases that offer insights to customers equip them with decision-making aids. These aids may be delivered as suggested next steps, aberrational activities, benchmarks, or alerts. For example, a consumer products company created a Facebook Messenger chatbot to help shoppers determine a count of products they will need when throwing a party. To help its clients develop long-term investment strategies, an institutional bank provides inferences from models about investor trends, portfolio risk, and inflation that were generated using client data and external data sources. 
• Action: Use cases that inspire action favorably change a situation for the customer. For example, with data it collects from sensors on its machines, an equipment provider predicts potential equipment failures and proactively replaces parts to reduce unplanned disruptions. One consumer retail manufacturer created a model to detect outliers in the sales patterns for specific products; the manufacturer uses the model to identify strategies to increase product sales by company retailers, who receive implementation support from company salespeople. 

All three types of use cases—those based on data, insight, and action—help customers solve problems; however, in data- and insight-based wrapping, the realization of value is dependent on the customer. Action-based use cases more reliably lead to benefits because the company plays an active role in the customer’s problem-solving process. In effect, a company achieves the strongest level of vertical integration through action-based data wrapping. It enables the company to better understand the value created for the customer; and to recognize value the company can potentially capture when the use case is executed and better position itself to do so. 

THE TWO KEY CAPABILITIES DATA WRAPPING REQUIRES 

Regardless of where data wrapping falls along the customer journey, all data wrapping requires two key capabilities to generate customer value: analytics and customer intimacy. 

• Analytics represents data, data science tools and techniques, and analytics-savviness; these help the company create analytics-fueled customer-facing features and experiences. The higher the quality of analytics, the easier it is to make use cases market ready. A high-quality analytics capability is dependent on a company being both digitized (i.e., having master data and integrated systems) and digital (i.e., possessing a digital offerings platform with access to reusable digital business components).[foot]J.W. Ross, C.M. Beath, and I.M. Sebastian, “Digitized ≠ Digital,” MIT Sloan CISR Research Briefing, Vol. XVII., No. 10, October 2017, https://cisr.mit.edu/publication/2017_1001_DigitizedNotDigital_RossBeathSebastian.[/foot] This capability leverages analytics-savvy technologists and product managers who can effectively ideate data wrapping use cases, assess the feasibility of wrapping scenarios, and execute sophisticated analytics using advanced methods. 

• Customer intimacy represents customer connections and customer knowledge, which combined help the company achieve a current, accurate understanding of customer needs and actual behavior. A company establishes customer connections in a variety of ways: customer touchpoints (call centers, the company’s salesforce); ecosystem partners (purchased customer demographics or psychographics, shared supply chain data); customer involvement (co-creation, pilots, advisory boards); digital technologies (Facebook pages, mobile apps); and the offerings themselves (via sensors). All of these connections create opportunities to acquire customer data that feed the company’s knowledge about its customers’ demographics, sentiments, context, usage, and desires. 

Wrapping capabilities (analytics and customer intimacy) help companies build solutions that meet customer needs. Our research shows that both capabilities are required to maximize value—either customer intimacy or analytics alone will fall short of creating an excellent data wrap. This happens because wrapping use cases grow in value as they become more tailored to the customer and automated, and both analytics and customer intimacy are required to enable these characteristics (see figure 2). 

DATA WRAPPING AT COCHLEAR LIMITED 

Cochlear Limited (Cochlear), with 2017 annual revenues of $1.2 billion, is an Australia-based company that designs, manufactures, and provides implantable hearing solutions to customers around the world.[foot]In 2017, Cochlear reported above-average net profit margins and return on assets. Cochlear Limited – company summary report. OneSource. OneSource Information Service, Inc. Retrieved from OneSource Global Business Browser, October 18, 2017.[/foot] The solutions combine a surgically inserted implant and an external sound processor. 

In September 2017, Cochlear launched its latest generation behind-the-ear sound processor, the Cochlear™ Nucleus® 7 Sound Processor.[foot]Cochlear and Nucleus are either trademarks or registered trademarks of Cochlear Limited.[/foot] The offering was developed in collaboration with Apple[foot]Steven Levy, “How Apple Is Putting Voices in Users’ Heads—Literally,” Wired, August 2, 2017, https://www.wired.com/story/how-apple-is-putting-voices-in-users-headsliterally/.[/foot] to establish interoperability with iPhone technology, allowing Cochlear to deliver features to end customers via mobile device. The processor offers the SCAN Scene Classifier feature, which applies algorithms to analyze a user’s environment (e.g., crowded street corner, quiet room) and automatically adjusts the sound processor’s settings to deliver the best hearing for the conditions. Changes to processor program settings had previously been made manually by the patient, but product use data suggested that patients may not always choose the optimal settings for the situation. Thus, developers designed the SCAN feature to make adjustments automatically (an action-based wrap). The developers did this by creating a scene classifier algorithm that recognizes distinct contexts and makes tailored processing adjustments. 

Some product features add value to a subset of customers. For example, a Cochlear implant system contains both internal and external coils that transmit electrical impulses to the implant. A coil operation feature tracks the amount of time that a person does not receive sound, referred to as a “coil-off” event. Such events are most common in children with a newly implanted solution: not yet comfortable with the processor, they might regularly displace it as they learn how to use it. The coil operation feature provides feedback to parents and caregivers, indicating how well the child is adapting and whether a different device might provide better retention (an insight-based wrap). 

Cochlear connects with customers (customer connections) and gathers customer information (customer knowledge) through traditional market research, patient focus groups, and clinical trials. Additionally, product managers schedule travel time to visit clinics and talk to customers, and they meet regularly with analytics colleagues to interpret processor usage data. Further, Cochlear employs people who experience the customer journey firsthand. Senior Product Manager Roger Smith wears a Cochlear implant: “People with normal hearing cannot truly understand what a Cochlear implant recipient experiences. I think it’s a huge advantage for the business to have people like me providing feedback [about recipient needs].” 

CREATING CUSTOMER VALUE WITH DATA WRAPPING 

Sophisticated analytics permit Cochlear’s customer connections and knowledge (customer intimacy) to help product managers identify dozens of use cases that could enhance customer value. Advanced algorithms and digital systems combined with the skills of analytics-savvy product and data employees (analytics) enable the viability of many of the company’s use cases and guide use case choices. 

To be purposeful in its choices, Cochlear product management has established priority business goals. In one example, to drive brand choice and market share, the company has honed a focus on functionality that would add value for implant candidates. Product management also weighs opportunities against effort, time, and resource requirements, and considers opportunities for technology reuse. In some cases, technology that has evolved over time to help Cochlear understand and improve products is relatively straightforward to transition to new customer-facing purposes. Finally, product management articulates a revenue model to ensure that new functionality creates revenue, and determines whether a feature will be part of a core offering. Cochlear chose to embed the SCAN and coil-off features in its core product, with the expectation that the features would increase candidate conversion rates. The choice is aligned with the cochlear implant reimbursement model in key markets. 

Cochlear’s success in data wrapping has inspired continued investments by the company in analytics and customer intimacy capabilities. According to Roger Smith, “With each win, with each successful use of customer insight data, we get more buy-in, a better understanding of how valuable this is, and more funding and resources—all of this to give our customers an above-and-beyond experience.” 

SETTING THE STAGE TO ENABLE YOUR DIGITAL GOALS 

For decades, digitized companies have used analytics to improve core business processes and generate financial returns through operational efficiencies. As companies become digital, they must embrace another approach to data monetization: data wrapping. Successful digital companies use analytics to delight customers and generate financial returns through sales of tailored products and services. If being digital is your goal, then this is the time to establish data and analytics that can be used in customer-facing ways, and to identify customer needs based on customer knowledge rather than assumptions. This will allow product and service owners to identify and deliver valued solutions to the marketplace.