Percentage of processes digitalized by – Obvious, rapid decisions based on a single version of the 27% incumbent consumer industry companies. truth, driven by undisputed facts; time to action is reduced by a factor of ten. Percentage of processes digitalized by 10 50% consumer industry disruptors. Case Study: StitchFix – Enhancing Style with Data Science Case Study: Voodoo Manufacturing – The Power of This San Francisco-based on-demand styling service and Combinatorial Technology apparel subscription company marries predictive data science with human skills to create a virtuous cycle that achieves and sustains consumer relevance by unifying sales, marketing, To borrow a software development term, the R&D and supply chain. The 80+ data scientists link every future of manufacturing is agile, not waterfall. aspect of operations. Algorithms guide human stylists to the clothing choices that clients are most likely to enjoy and purchase. Simultaneously, data science informs the supply chain, determining the logistical flow that optimizes delivery to Jonathan Schwartz – Co-founder of Voodoo Manufacturing the client’s door. Finally, live feedback from clients generates Voodoo Manufacturing, the New York-based 3D printing a vast amount of consumer preference data by clothing start-up, uses combinatorial technology to continually characteristic, which the company uses to predictively design 11 improve production efficiency on a manufacturing floor that its private label line. seamlessly melds human technicians, robots, 3D printers, AI and other technology. In-house design software manages and coordinates the process from order to shipping. Machine Case Study: Farmers Business Network – Unlocking learning increasingly streamlines processes. Voodoo is adding Agribusiness Value through Data Sharing robotics to automate tasks currently performed by technical staff (for instance, robots “harvest” completed printing plates Farmers Business Network (FBN) is a US-based analytics and and put clean ones in the printer). In the future, they believe commerce platform that crowd-sources data from farmers to robots will clean parts, ensure quality and automate packing help farmers make better decisions. Participants contribute and shipping, while human technical support troubleshoots their individual data, which is consolidated into a significant and continually enhances the effectiveness of the line. and powerful base of knowledge. This collaboration allows Next to technology adoption, a data mindset and all participants to benefit from the shared insights across analytical capabilities will be the most significant factors the platform. FBN farmers generate 9% higher corn yields in determining future success: these are the building blocks and 11% higher soy bean yields than average, illustrating for enabling technology and understanding customers and how good data and information enable this community to consumers. While few companies dispute the importance of make better decisions to increase output. Additionally, FBN data, most have not yet gone through the dramatic change offers the first national e-commerce buying system for farm necessary to become truly data-driven organizations. Future inputs, premiums for speciality crops, and access to credit operating models will view and incorporate data as DNA, the programmes. While some farmers are at first hesitant to share fundamental ingredients for the entire organization, governed information with competitors, FBN has expanded primarily by a top-down mandate and actively supported by every through word-of-mouth as farmers realize the benefits to be employee. Serving the core, consumer-obsessed purpose had in terms of profits of the digital farm economy and gain of the company will require significant increases in individual strength in numbers during big agriculture’s era of mega- consumer insight. As the pace of change accelerates, consolidation. dramatically expanded and continually renewed data becomes vital to survival. Data will be the vital factor enabling leaders and Structure: The Fundamental Change in Shape individual employees to make the best decisions at the optimal and Execution within the Operating Model speed. Imperatives for the data-driven organization include: Ecosystem – Top-down mandate, with leadership themselves actively Operating models of the future will be transformed using data, driving its improvement and extending data as structurally, bringing ecosystems to the core of companies’ DNA to every member and structural component of the strategies. Extending far beyond the existing supplier/ organization customer value chain relationships, an ecosystem is the – Exponential insights aided by data science and a real-time network of cross-industry players who work together to data system across every function and role within the company define, build and execute market-creating customer and consumer solutions. An ecosystem is defined by the depth – Centrally facilitated and seamless flow of data across and breadth of potential collaboration among a set of business models, functions and project teams players: each can deliver a piece of the consumer solution, or contribute a necessary capability. 10 Operating Models for the Future of Consumption