Monthly Archives: May 2016

Revolutionize food chain

The way digital technologies are reshaping the relationship between consumers and brands has been hotly debated over the past few years, with much discussion of the reshaping of consumer decision journeys, the advent of multichannel marketing and sales, and the impact of smartphones and the mobile Internet on customer behavior. Yet an even bigger opportunity has been largely overlooked. By taking advantage of big data and advanced analytics at every link in the value chain from field to fork, food companies can harness digital’s enormous potential for sustainable value creation. Digital can help them use resources in a more environmentally responsible manner, improve their sourcing decisions, and implement circular-economy solutions in the food chain.

Huge untapped potential

So far, most of the excitement about digital’s potential in the consumer-packaged-goods industry has centered on marketing and sales. But for food producers, the opportunities begin higher upstream and end lower downstream. At the upstream end, the agricultural practices followed by dairy farmers, cacao and coffee producers, wheat and barley producers, cattle farmers, and so on result in enormous variations in commodity costs in an industry where raw materials represent easily 60 percent of the cost of goods sold (COGS) (Exhibit 1).

Manufacturing and packaging also represent a substantial share of COGS, as well as contributing to companies’ environmental and social footprints and food-safety risks. At the other end of the food chain, big data and advanced analytics can be used to optimize downstream activities such as waste management. Food waste causes economic losses, harms natural resources, and exacerbates food-security issues. About a third of food produced for human consumption is lost or wasted every year in a world where 795 million people—a ninth of the population—go hungry (Exhibit 2).

Digital strategy for insurances

images-14The nature of competition in property and casualty (P&C) insurance is shifting as new entrants, changing consumer behaviors, and technological innovations threaten to disrupt established business models. Though the traditional insurance business model has proved remarkably resilient, digital has the power to reshape this industry as it has many others. Innovations from mobile banking to video and audio streaming to e-books have upended value chains and redistributed value pools in industries as diverse as financial services, travel, film, music, and publishing. As new opportunities emerge, those insurers that evolve fast enough to keep up with them will gain enormous value; the laggards will fall further behind. To succeed in this new landscape, insurers need to take a structured approach to digital strategy, capabilities, culture, talent, organization, and their transformation road map.

Though the P&C insurance business has long been insulated against disruption thanks to regulation, product complexity, in-force books, intermediated distribution networks, and large capital requirements, this is changing. Sources of disruption are emerging across the value chain to reshape:

  • Products. Semiautonomous and autonomous vehicles from Google, Tesla, Volvo, and other companies are altering the nature of auto insurance; connected homes could transform home insurance; new risks such as cybersecurity and drones will create demand for new forms of coverage; and Uber, Airbnb, and other leaders in the sharing economy are changing the underlying need for insurance.
  • Marketing. Evolving consumer behavior is threatening traditional growth levers such as TV advertising and necessitating a shift to personalized mobile and online channels.
  • Pricing. The combination of rich customer data, telematics, and enhanced computing power is opening the door to usage- and behavior-based pricing that could reduce barriers to entry for attackers that lack the loss experience formerly needed for accurate pricing.
  • Distribution. New consumer behaviors and entrants are threatening traditional distribution channels. Policyholders increasingly demand digital-first distribution models in personal and small commercial lines, while aggregators continue to pilot direct-to-consumer insurance sales. Armed with venture capital, start-ups like Lemonade—which raised $13 million in seed funding from well-known investors including Sequoia Capital—are exploring peer-to-peer insurance models.
  • Service. Consumers expect personalized, self-directed interactions with companies via any device at any hour, much as they do with online retail leaders like Amazon.
  • Claims. Automation, analytics, and consumer preferences are transforming claims processes, enabling insurers to improve fraud detection, cut loss-adjustment costs, and eliminate many human interactions. Connected technologies could allow policyholders and even smart cars and networked homes to diagnose their own problems and report incidents. Self-service claims reporting such as “estimate by photo” can create fast, seamless customer experiences. Drones can be used to assess damage quickly, safely, and cheaply after catastrophes.

 

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All these disruptions are being driven and enabled by digital advances, as Exhibit 1 illustrates with examples from auto insurance. No single competitor or innovation poses a threat across the entire value chain, but taken together, they could lead to the proverbial death by a thousand cuts: many small disruptions combining to fell a giant.

Data enablement for the common good

The tremendous impact that digital services have had on governments and society has been the subject of extensive research that has documented the rapid, extensive adoption of public-sector digital services around the globe. We believe that the coming data revolution will be even more deeply transformational and that data enablement will produce a radical shift in the public sector’s quality of service, empowering governments to deliver better constituent service, better policy outcomes, and more-productive operations.

The data revolution enables governments to radically improve quality of service

Government data initiatives are fueling a movement toward evidence-based policy making. Data enablement gives governments the tool they need to be more efficient, effective, and transparent while enabling a significant change in public-policy performance management across the entire spectrum of government activities. As Exhibit 2 shows, data applications can transform operations and service delivery in everything from tax compliance and collections to economic development to healthcare to education—and much more.

To raise quality of service, optimization applications are necessary but not sufficient in themselves. Governments also need to deploy a comprehensive and open performance-management system: data enablement provides a solid fact base for policy making while allowing transparency and public accountability. With this perspective in mind, governments need to launch data initiatives focused on:

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  • better understanding public attitudestoward specific policies and identifying needed changes
  • ƒƒdeveloping and using undisputed KPIs that reveal the drivers of policy performance and allow the assignment of targets to policies during the design phase
  • ƒƒmeasuring what is happening in the field by enabling civil servants, citizens, and business operators to provide fact-based information and feedback
  • evaluating policy performance, reconciling quantitative and qualitative data, and allowing the implementation of a continuous-improvement approach to policy making and execution
  • ƒƒopening data in raw, crunched, and reusable formats.

The continuing and thoroughgoing evolution taking place in public service is supported by a true data revolution, fueled by two powerful trends.

First, the already low cost of computing power continues to plummet, as does the cost of data transportation, storage, and analysis. At the same time, software providers have rolled out analytics innovations such as machine learning, artificial intelligence, automated research, and visualization tools. These developments have made it possible for nearly every business and government to derive insights from large datasets.

Second, data volumes have increased exponentially. Every two years the volume of digitally generated data doubles, thanks to new sources of data and the adoption of digital tools. And a new explosion of data is on the horizon, thanks to the wide-scale deployment of connected devices, which are expected to increase from 10 billion in 2013 to 50 billion by 2020.1Many of those devices will be associated with smart-city programs, such as sensors embedded in streets and other public areas. By 2020, smart-city usage in European cities2will generate 100 e-bytes of data per day—four times more than the global data generated daily from all usages in 2015.

Even without the data generated by connected devices, data enablement is already making a difference. A few examples suggest just how big that difference is.

Smart defense. One large national-defense organization increased equipment and weapons-systems readiness and availability through a data-enabled redesign of spare-parts sourcing and supply strategy. Data-analytics engines provided full transparency on the performance and fully loaded costs of spare parts, while also allowing analysts to simulate the impact of modifications in sourcing and supply strategies. The redesign produced optimized expenditures equal to 10 to 12 percent of the country’s overall military operations and maintenance budget.

Smart policing. An advanced-analytics engine has enabled several major cities to improve the quality of police services and prevent threats from organized crime and terrorists. One of the tools was analysis of factors suggesting imminent gang activity, such as four or more Twitter posts from gang members within ten minutes.

More broadly, these cities integrated and analyzed open-source data (such as social media) and traditional police data to monitor public sentiment in order to provide early warning of actual or potential criminal activity and enable targeted and appropriate intervention; continuously track city-specific threats from organized crime and terrorist organizations; and monitor and preempt the potential radicalization of local populations.