State of Transformation: Making the Pivot to Digital

12/21/2017

Since there currently is no single definition of “digital enterprise” accepted throughout the industry, the idea of “digital process innovation” is more a theoretical goal than a realistic one.

Consumer goods companies want to drive digital transformation, but there is still uncertainty about process definition and desired outcomes. Recent research conducted by Supply Chain Insights finds that 49% of companies have undertaken a digital strategy in either revenue management, trade promotion or consumer/customer engagement (see Figure 8).

An organization’s digital strategy is often an extension of its digital marketing: use of social media, ratings/review data, digital advertising, micro-media strategies, localized assortment, sentiment analysis and online strategies. These practices represent a fundamental shift by the enterprise to sense and serve consumers from the outside in.

The focus is on both speed and quality of response. This is difficult when processes are anchored on the enterprise — inside-out, centered on data sources with weeks of latency. Few companies have as yet aligned to drive a full cross-functional digital transformation. Here are a few options for achieving this evolution:

Autonomous Process Sensing: Automating business processes through cognitive learning and artificial intelligence reduces labor and the need for people to “touch” data. We are three to five years away from redefining trade promotion through cognitive computing.

Value Chain “Uberization": This means building platforms to enable shared resources across a community. This can include a platform for commonly used materials like pallets, display racks and delivery trucks.

E-Commerce and Cross-Channel Response: Redesigning channel response can maximize the value of e-commerce and shifts in shopping behavior. This includes maximizing test and learn, which lets companies evaluate packaging, product assortment and artwork through e-commerce before deployment. Knowing the e-commerce shopper — age, sex, and other demographics — enables in-vitro testing and learning.

Internet of Things: The use of machine-to-machine streaming data improves outcomes by facilitating real-time response. This can include the quality of cold-chain delivery and sensing replenishment for vending machines, food service dispensers, and the store shelf.

Listening/Cloud-Based Computing: Using unstructured data (social sentiment, warranty and quality) improves organizational productivity and enables outside-in processes to be market-driven. More mature companies have cross-functional groups organized to respond to a listening post. The demand-driven value network is maturing into a market-driven one.

To improve channel response in a digital transformation, companies must be more aggressive about overcoming the barriers noted in Figure 9.

One major opportunity for digital transformation is the integration of new technologies that can improve analytics, mobility, social listening, consumer sensing and in-store sensing. (For example, how can companies use pictures generated by in-aisle robots to identify out-of-stocks? Or how can teams more aggressively test and learn across channels to better tailor trade promotions?)

The possibilities are endless, but only if consumer goods companies can align cross-functionally through a focus on the shopper. For many, this is still a major hurdle. 

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