What are the issues with Supply Chain Digitalization, without a Bionic approach?

15 de abril de 2020

3 minute read

This is an excerpt from the paper “Building the Bionic Supply Chain”, focused on the issues related to the topic above.

BCG — Boston Consulting Group
By Pepe Rodriguez, Frank Cordes, Rajesh Shetty, Jens Jahn, Llorenç Mitjavila, and Stefan Gstettner
Edited by Joaquim Cardoso
APRIL 14, 2020

The Digital Dilemma

Over the past decade, digitization has helped improve many supply chain functions.

Firms have deployed automation, advanced analytics, and artificial intelligence (AI) to optimize the value of supply chain operations for specific use cases, including demand forecasting and production scheduling.

Today, supply chain functions such as planning, manufacturing, and distribution are semiautonomous in many companies.

Yet even today’s most digitally developed supply chains are far from realizing their promised benefits. Various interrelated challenges stand in the way.

For starters, the organization model is still siloed. Demand planners, logistics managers, schedulers, and other employees tend to be more focused on optimizing their own subfunction’s performance than the E2E supply chain’s.

Organization structures and incentive systems that focus on functional performance exacerbate these obstacles.

And resistance to change hasn’t helped matters.

As a result, collaboration between humans remains underdeveloped.

Data has greatly enhanced visibility across the E2E supply chain, and platform organizations have made cross-functional decision making easier.
But the KPIs that guide decisions are frequently in conflict with one another. For example, manufacturing’s metrics aim for low production costs with large batches and few changeovers, whereas the customer supply chain requires high flexibility and thus small batches and frequent changeovers.

Consequently, it can be difficult to make decisions that will optimize overall supply chain performance.

Emerging technologies pose an additional challenge. New analytics solutions have the potential to improve the speed and quality of decision making.

But adoption is slow because some of these solutions are seen as black boxes whose inner workings are hard to grasp and as a result are untrustworthy. So it’s not surprising that many supply chain operators don’t feel comfortable using these technologies.

Organizations also must contend with data problems.

In many companies, data is trapped in core systems, such as ERPs. This limits the accessibility of the data and therefore the value that can be extracted from it. While data platforms have eased that pain somewhat, firms still have trouble scaling and developing their data assets.

Key messages of the full version of the paper

To capture the greatest value from their end-to-end (E2E) supply chains, companies need to adopt a bionic operating model.

Building a bionic supply chain requires a comprehensive digital transformation where employees as well as leaders play crucial roles.

Although the size of the effort is enormous, a bionic supply chain can lead to substantial improvements in performance. (1) It can boost revenue by 4% to 6%, (2) customer service levels by 5 to 30 percentage points (pp), and (3) EBITDA by 2 to 4 pp. (4) Moreover, a bionic supply chain has the potential to reduce manufacturing, warehousing, and distribution costs by 10% to 20% and (5) working capital by 15% to 30%.

It’s also more able to react swiftly to sudden changes in demand, supply prices, trade policies, and so on-perhaps the most important consideration of all in the current business environment.

The bionic supply chain operating model, a major step forward from the digital supply chain, addresses these issues.

To ensure that they leverage each type of collaboration to the fullest extent possible, companies need to revisit four elements of their supply chain operating model. (1) KPIs; (2) The Platform Organization; (3) Digital Skill Building and Talent; (4) The Data and Digital Platform.

BCG research clearly demonstrates that a strong focus on people and processes is key for a major change initiative like digitization.

We’ve found that five practices are especially important for a successful bionic supply chain implementation. (1) Put Employees at the Center; (2) Double Down on Leader Alignment and Enablement; (3) Set Up a Transformation Management Office; (4) Develop a DDP Strategy and (5) Continually Scrutinize.