Tech Trends 2017: A Consumer products perspective

Mixed Reality: Bringing experiences to life for consumer products organisations

As innovation drives new technology options, organisations embrace Mixed Reality to connect with consumers in novel ways. It is too soon to predict when mixed reality will establish itself as a ubiquitous technology but momentum is clearly building as investors continue pouring significant funding into product development, and consumer products companies deliver innovative projects to the market. To stay relevant when mixed reality hits full stride, consumer products companies should be making preparations now in anticipation of what is to come.

The disruptive potential of mixed reality is incredible—and exciting. Consumer products companies have the opportunity to approach advertising, marketing, and the retail experience with completely new and intriguing ways to attract consumer attention. As the technology evolves and adoption accelerates, consumers are likely to embrace the immersive, visually rich, and personalised experiences readily, triggering yet another shift in not only how brands engage consumers, but in how we define success for consumer products companies.  

Back to top

Everything-as-a-Service: A paradigm shift for consumer products

A new business imperative is helping shape shaping strategic and operational decision making: The shared economy is taking hold at the enterprise level. Just as ride-sharing companies leveraged technological advancements, shifts in consumer behavior, and a flexible, on-demand workforce to create new opportunities in transportation-as-a-service, many corporations are reimagining the very nature of their offerings—to customers, suppliers, internal constituents, and competitors—as services.

XaaS is already showing clear emerging signs of the potential to provide tremendous upside to consumer products companies. Whether achieving cost savings through operational efficiencies or topline growth through building net-new revenue opportunities, leaders must identify the potential positive and negative impact on their businesses. How these impacts will be realised depends on the approach to evaluating and executing opportunity areas. The consumer products XaaS framework and the XaaS playbook provide guidance on how to think about this broad and evolving trend so leaders can properly approach XaaS and leverage it to their organisation's advantage.

Back to top

Dark Analytics: Leveraging insights hidden within data

With ever-growing data reserves still unexplored, aggregation, analysis, and storage are no longer end goals in the agile organisation's analytics strategy. Going forward, analytics efforts are expected to focus on illuminating powerful strategic, customer, and operational insights hidden within non-traditional and "dark" data sources for CPG companies. Be excited about the potential of unstructured and external data, but it's important to stay grounded in specific business questions such as consumer sentiments, shopper behavior, assortment optimisation, innovation, brand health and promotional feedback with bounded scope and measurable, attributable value. Consider these questions to help focus your dark analytics efforts on areas that matter to your business—and to avoid getting lost in the increasingly vast unknown.

¹Exponential Watchlist
²These capabilities represent just three of the levers within Doblin's 12 Levers for Breakthrough Innovation framework 

Back to top

Exponentials Watch List: Embracing innovation in consumer products

A recent Deloitte study, Exponential Watchlist¹, looked at 44 leading consumer products firms and found that those that are able to effectively build systematic innovation capabilities have been more successful embracing exponential change. The capabilities that successful innovators have adopted at a rate that outpaces their peers include funding, metrics, and incentives². These three levers have been grossly underappreciated by other consumer products leaders, with only 32 percent, 43 percent, and 45 percent (respectively) of firms studied demonstrating these capabilities. This presents a clear path for large consumer products companies to better position themselves to embrace exponential technologies.

It takes a highly disciplined approach and effort to embrace innovation and reap the rewards. What gives us grounds for optimism is that we see Evidence of some companies achieving innovation and harnessing the power of exponentials gives us grounds for optimism. Those companies exhibit several common characteristics: systematic use of distinct funding mechanisms, incentives, and metrics. Organisations who share these characteristics are more likely to foster successful innovation. Those companies—and their delighted customers—can be considered winners no matter what "next big thing" hits the consumer products industry.

Blockchain: Putting the trust economy to work for consumer products

Blockchain offers many benefits including removing silos between parties and internal functions, streamlining business and consumer payments, improved security through transparency. Consumer products companies have been slow to adopt these use cases and to embrace collaboration between market participants to date; however, as with many emerging technologies, higher levels of adoption will increase mutual benefit. As we wait for critical mass, consumer products companies should assess and prioritise Blockchain use cases within their landscapes; while maximum benefit may be derived through broad market adoption, non-market-dependent benefits such as streamlined payment processing, internal data sharing and differentiated consumer transaction methods will reward those who move boldly into the Blockchain future.

Back to top

Machine Intelligence, cognitive automation and robotics process automation (RPA)

Machine learning, cognitive analytics, robotics process automation (RPA), and bots are among the newest wave of advanced analytics capabilities, collectively known as artificial intelligence (AI). These capabilities are being widely leveraged in the consumer goods marketplace to gather consumer insights, optimise inventories, and create offerings for retail customers.

Machine learning and RPA can be leveraged for many consumer goods applications that require insights beyond those delivered by traditional analytics techniques. Building machine learning and artificial intelligence capabilities in house may appear challenging, but the value delivered by deploying these methodologies to high-impact business issues warrants adoption and investment. Because machine learning methodologies adapt over time to better draw insights, the value delivered by an AI or machine learning use case will continue to grow and improve over time.

Back to top