Solving the ‘Wicked Problems’ of S&OP with AI

Wicked problems are undermining sales and operations planning (S&OP) and the supply chain.

Denise Byers

Wicked problems are undermining sales and operations planning (S&OP) and the supply chain. They are characterized by extreme complexity and deep root causes that defy conventional solutions.

As described by the Harvard Business Review, wicked problems are “the opposite of hard but ordinary problems, which people can solve in a finite time period by applying standard techniques. Not only do conventional processes fail to tackle wicked problems, but they may exacerbate situations by generating undesirable consequences.” That’s exactly what’s been happening with S&OP programs at large global companies in CPG, industrial, pharmaceutical and other industries. Companies are falling short in their efforts to fulfill S&OP objectives — to connect back-end supply chain sourcing, production and distribution processes with external-facing sales, marketing and customer management ultimately suffering from low S&OP maturity levels. What’s the culprit?

The Devil is in the Data

Data is the root cause of the wicked problems in S&OP. It is complex, scattered and not real time. Information today is extraordinarily complex, high volume and accumulates at breathtaking speed. S&OP depends on data from ERP, CRM, planning, sales, marketing, warehouse management, partner systems and other applications — nearly the complete universe of business applications at large global enterprises.

Scattered across systems causes data to be siloed and fragmented. Companies may move it into a data warehouse or data lake, but then face the challenge of sorting the wheat from the chaff. What data is relevant, and which is not for S&OP? It’s a critical question given rising data volumes, yet attempting to answer it ends up being a massive, time-consuming and costly ordeal.

Even with some success, the data could be out of date by days, weeks or even months. Meanwhile, conditions in sales or in the supply chain change faster than you can snap your fingers. Companies end up making decisions based on outdated information — not real-time data that reflects the volatile dynamics of the business.

The result? Stakeholders don’t have a single version of the truth and debate over what data is right, consuming precious time and money.

A New Approach to S&OP’s Wicked Problems

A new approach is needed to solve the wicked problems of S&OP. That’s where cognitive automation— powered by artificial intelligence and machine learning— enters the picture. It’s time to turn data collection and analytics over to the machines, so that planners and executives can focus on making intelligent decisions.

This cognitive technology can crawl enterprise applications in near-real time, consolidate and normalize data in a cognitive data layer and apply AI and ML algorithms to extract insights. It removes from S&OP stakeholders the near-impossible task of aggregating information and generating actionable insights.

This technology is able to predict scenarios and recommend actions to truly optimize S&OP. It has thepotential to pinpoint an issue at a warehouse or a supplier that would otherwise be overlooked, or not detected for many weeks.

S&OP as a Critical Part of Digital Transformation

Cognitive automation can bring transformational benefits to S&OP and supply chain operations at top Fortune 100 companies. Large multinationals can easily increase inventory turns, preserve working capital, align sales forecasts with sourcing and production and better meet service-level metrics for on-time and in-full delivery.

Powered with AI, this automation will anticipate disruptions, detect issues before damage is done and prescribe actions to mitigate impact. It will make S&OP truly strategic and supply chains resilient, aligning the entire organization around a business plan and providing  measurement and flexibility to adapt to marketplace changes.