How supply chains are innovating to combat challenges

Learn how business planners are using advanced data, analytics and forecasting capabilities to navigate supply chain disruptions.

Supply chain management is famously complex even in seemingly “simple” times. And of course, these are not simple times.

Lockdowns, inflation, war … what’s next? These seismic changes have upended the intricately connected global supply infrastructure, putting intense new pressures on product delivery, suppliers, customer satisfaction and bottom-line margins.

The truth is, though, supply chain challenges didn’t start with the pandemic. The increasingly intertwined global network of manufacturers, suppliers, shippers and customers was already pressuring business planners to be more innovative and forward-thinking. That’s why leading companies have been leaning into advanced data and analytics to optimize their supply chains and gain a serious competitive edge.

But advanced data and tech alone are not the cure-all for planners trying to manage margins in this “what’s next?” world. Finding the right balance between supply and demand these days—and staying competitive—will require companies to rapidly innovate and establish some essential new capabilities, as we outline in two reports, Supply chain innovation and Get ahead of demand.

The new rules of innovation

Optimizing the balance between supply and demand is one of the age-old laws of business. Getting it right today requires the finance and operations teams to manage a highly complex mix of variables that looks very different than even a decade ago: product types, customer profiles, price sensitivities, delivery options, locations, and a whole cost of goods menu in which the options and prices change by the hour.

And somewhere in that ever-changing mix is the optimal intersection of customer and business needs. To find it, at a very high level, planners need to start by doing three fundamental things:

  1. Determine the actual cost of complexity down to the lowest level of detail for every product, customer, and order.
  2. Identify the root cause of any excessive complexity so that it can be resolved.
  3. Simulate what will happen when different actions are taken, no matter what the mix of variables or related complexities.

Establishing this big picture view is an essential first step toward innovation. It can be the difference between investing in the right new product versus eliminating the wrong one, for example, or correctly prioritizing the most valuable customers over the least.

The skills to sustain

The framework also helps companies identify the capabilities they will need to meaningfully innovate and optimize their supply chains—the operational expertise; emerging technologies; and advanced data, analytics, and predictive models that can transform their current supply chain management processes.

Data engineering

Advanced technologies like artificial intelligence (AI) and machine learning are making it faster and easier to collect both internal and external data, identify what is useful, and make it consistently available for predictive models and algorithms to mine for new insights. 

Real time simulations

All of that sophisticated data and tech won’t matter without a robust way to model it and do scenario analyses. Running simulations in real time to evaluate the potential impact of multiple “what if” scenarios enables rapid review of the choices available to planners, and the optimal actions.

Ongoing monitoring

Market conditions continue to change rapidly—new prices, commodity costs, exchange rates, customer preferences—and planners must quickly identify those changes and incorporate them into the supply chain platform. Many companies now use automated models to identify key changes and feed them into the platform.


From capabilities to actionable insights

Improving the ability to forecast supply and demand—and to do it faster and more accurately—has a material impact on revenue, operating margins and customer satisfaction, to be sure. But it’s becoming increasingly important to staying competitive, and especially in a business climate in which the only certainty seems to be rapid change.

The advanced data, technologies and forecasting capabilities needed to innovate the supply chain are on-the-ground, established tools that leading companies are using to move from manual spreadsheets to intelligent demand forecasting.

Broadly, intelligent demand forecasting matches the innovation framework and capabilities defined above with the right data and predictive models, and then leverages AI and machine learning to process all of the potential complexities and scenarios at a speed that humans and their spreadsheets simply cannot match. Better still, it liberates the planning team from time-consuming manual data collection and reconciliations, opening up more bandwidth to analyze the results and develop appropriate action plans.

In our work with clients on intelligent demand forecasting, we’ve learned that best practices include:


Clearly defining business drivers at a granular level that is unique to each product and line of business, rather than just an overall top-level view.


Identifying both internal and external data signals that drive value. Historical company data is hugely important to building effective models, but external data like weather and local market patterns can further sharpen forecasting accuracy.


Finding the right predictive models for each task in the forecast. Many companies will test hundreds of models against each other before choosing the right three or four that best deliver their specific forecast needs.


Creating a continuous feedback loop that helps the models—and, yes, the humans, too—get steadily smarter and more accurate with the ongoing demand planning.

Perhaps most important: Intelligent forecasting is no longer some rosy vision of the future for business planners, but it is now a proven, battle-tested way to innovate and optimize the supply chain.

Contact us

Chris Gottlieb

Chris Gottlieb

Principal, Supply Chain & Operations Advisory, KPMG US

+1 201-417-6025