Tech Trends 2017: Moving to Outside-in Supply Chain Processes

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Tech Trends 2017: Moving to Outside-in Supply Chain Processes

By Lora Cecere - 10/24/2017

Today, the word “digital” drips from the tongues of technology providers and consultants. But without a common industry definition of what that involves, it’s hard to make any digital plans actionable.

For the business user, the goal is growth, of course. For the technologist, with slowed spending on enterprise resource planning, the goal is to create a new market opportunity. But digital market transformation is happening more slowly than was expected by many technology providers, consultants and analysts, as shown in Figure 1.

Figure 1, supply chain

Digitization transforms businesses. And the most successful transformations redefine business models. A digital business model uses new forms of technology to create new streams of revenue and business value. It’s about combining technologies to sense market changes in real time and shape a more meaningful output. 

Digital business is about much, much more than the redefinition of business processes for business-to-business or business-to-consumer. E-business strategies are foundational and necessary, but digital business goes beyond e-business. Today, B2C models are well defined, but B2B processes lag behind: Only 9% of B2B commerce flows through business networks.

When executed correctly, digital business strategies are transformative. Here are five examples:

Digital transportation and logistics: Telematics and the use of global positioning systems have changed the lives of truck drivers in their cabs. They can see real-time traffic jams, view shifts in road closures and quickly check the status of vehicle maintenance. Likewise, the dispatcher can follow the truck’s position and expected time of arrival. Digital transportation is rapidly changing logistics.

Uber is a good example of a digital business strategy in transportation. While Uber currently powers a network of taxi and car services, its ultimate goal is to redefine the automotive supply chain, to replace automotive purchases with easy-to-use car services.

A parallel example is what happened with performance-based logistics in the world of aerospace and defense. This industry was redefined through collaborative sharing, and is shifting to autonomous vehicles for transportation and logistics and the use of the automobile as a social meeting place on wheels.

Digital process manufacturing: Predictive maintenance in process manufacturing is based on the mean time between equipment failure and the development of predictive schedules to perform maintenance before those failures occur.

Yet within the factory, sensors abound. Equipment purchased within the last decade runs by a programmable controller that tracks the “health” of machine-pump pressure, motor temperature, oil viscosity, and temperature and services machinery, when needed.

The digital manufacturing process is about redesigning through mobility, the internet of things and cognitive learning. Within process industries, only 5% of companies are attempting to use mobility within manufacturing and only 3% are using wearable devices.

Digital discrete manufacturing: In discrete manufacturing, parts are made to order. Traditional processes such as milling, casting and machining utilize subtractive manufacturing: materials decrease as the item is manufactured. Digital printing, or additive manufacturing, or 3D printing, changes that equation. 

In additive manufacturing, substrate is added to make the part. Discrete items are made based on digital images. Today, 15% of discrete manufacturers are actively pursuing 3D printing for production-based processes; for one, digital printing is increasingly being used for prototypes. The opportunity here is quick and easy production of each “unit of one.” Examples include specialized shoe inserts customized for each buyer and samples of packaging materials and parts.

Digital agriculture: Traditional agriculture is based on well-honed methods of planting, harvesting and food manufacturing. Digital agriculture is a step change. It’s the reason that John Deere tractors are now equipped with sensors to read a field’s moisture and temperature levels, and why manufacturers like Land O’Lakes are investing in test beds to use sensing technologies and advanced analytics to measure the soil, weather, crops, seed traits, fertilizers and additives; the testing identifies the best combinations to improve yield.

Digital path to purchase: In the consumer packaged goods industry, there are four “moments of truth” in the purchase cycle when marketers can influence decisions: when the shopper is making a list, when she’s putting the item into the basket, when she’s buying the product at checkout and when she’s talking about her experience on social media. 

Digital tools can help impact all four moments.

This automation of the digital path to purchase necessitates a real-time database of purchase behavior that combines point-of-sale data, loyalty information, and weather and store information; the ability to listen to consumer sentiment (ratings and reviews, Facebook posts, blog posts, etc.) requires the mining of unstructured text.

Today, only 9% of CPG companies have a cross-functional team to build the processes needed to yield insights from structured and unstructured data. We find that most efforts are bogged down by traditional customer relationship management solutions and a narrow definition of supply chain management. 

The clash of processes and technologies is a new state of normal. New roadmaps are not evolutionary based on best practices. Instead, they challenge current paradigms. Traditional enterprise flows are inside-out based on historic transactions; digital business flows are real-time and outside-in. New processes start with the channel and translate actual sales outside-in with low latency. These shifts are shown in Figure 2.

Figure 2, supply chain

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