When business starts to feel complex, our first instinct is to assert control — putting more measures in place to limit possible outcomes and minimize the variety of risks incurred. In some cases, however, our best efforts to make things easier actually make them more difficult. This scenario is playing out in countless business-to-business relationships.
B2B relationships have always been complex, and the supply chain is no exception. After all, there are more market nuances, more stakeholders, and more economies of scale to pursue and maintain. These partnerships have become even more complicated as enterprises have layered systems on top of them. Now, the system that vendors use to submit invoices might be completely separate from the system they use to track inventory — and both might differ from the system used to monitor and evaluate change orders.
As one might assume, this often creates inefficiency and confusion.
Some advanced software tools (such as a robust enterprise resource planning system) can help you do a better job of keeping these systems in line, but they don't solve a fundamental problem: Efforts to exert more control and precision over a supply chain often end up making it more complex.
The Cynefin Framework and Supply Chain Technology
As a business implements more solutions to address specific problems, the larger unbound problems become harder to see — you can't see the forest for the trees, so to speak. A helpful way to think about this is by using the Cynefin framework, which plots business challenges in one of four quadrants: chaotic, complex, complicated, and simple.
As supply chain relationships grow to include more and more complicated systems, the relationships themselves move into the "complex" quadrant. This means the correlation between cause and effect can only be seen in retrospect.
For example, let's say you're having a hard time tracking and estimating inventory. You can deploy sophisticated advanced supply chain management analytics, but that will only improve inventory predictions. It will help you react to problems, but it won't enable you to solve them. It won't tell you, for example, that your ordering system doesn't translate key information over to your vendor's platform, which results in inconsistent and unpredictable order fulfillment.
To truly optimize supply chain relationships, businesses must move from the "complex" Cynefin quadrant into the "complicated" Cynefin quadrant. There, according to the framework, parties can effectively and thoroughly analyze cause-and-effect relationships.
The best way to move between those quadrants, then? Leveraging technology.
Deploying Useful Technology in Supply Chain Management
Most of us already know that our partners across the B2B spectrum are eager for better technology. In fact, research by Episerver suggests that 84% of B2B decision makers view increasing digital expectations from their customers and partners as a top external threat.
Technology in supply chain and logistics doesn't deliver on those expectations very well, which hurts relationships. Recent data from Gallup shows that while about 20% of B2B customers experience problems with companies, only 5% of customers are satisfied with how those problems are resolved.
That's a result of these relationships being in the "complex" quadrant of the Cynefin framework: The problems aren't resolved effectively because their causes can't be identified until it's too late. Existing technology in supply chain and logistics is great at showing whether you're getting what you requested from vendors. But if you aren't seeing tangible benefits, individual technology solutions aren't great at showing you or your partners why.
Instead of deploying technology solutions that merely shine a brighter light on complex problems, how can businesses use technology solutions that help resolve these issues?
First Steps: Look Into the Data
What businesses should pursue is fully integrated digital relationships in their supply chain. Once technology is implemented broadly and consistently, you can begin to unravel the data that drives solutions. This might include:
- Work orders.
- Service and product descriptions.
- Shipping manifests.
- Work breakdown structures.
This data can be empowering for both your business and your supply chain partners. After all, eliminating complex systems is a win-win proposition — those transactions should become clearer and more efficient on both sides.
Oftentimes, B2B systems become complex because the humans involved fail to see certain unintended consequences. In a fully integrated relationship, tools such as artificial intelligence and machine learning provide a significant edge: They show internal and external stakeholders the causes and effects of each part of the supply chain meticulously and accurately.
Deploying these solutions at the holistic scale necessary to help B2B relationships is no easy task. It takes full buy-in from not only all stakeholders in your organization but also from key players in your partner organizations. The first steps should involve data: Figure out the story behind the complexity, and then start building solutions from there.
B2B relationships will certainly improve once you can identify the incentives that produce specific actions. Sometimes, the best way to do that is by taking a step back.