Imagine a business that runs better. “Better” looks like Integrated Business Planning—a harmonious framework in which sales, finance, and supply chain operations combine long-term profit goals and short-term demand planning efforts for a balanced, unified trajectory.
Right now, brands are implementing demand planning technologies to help their businesses achieve harmony during times of change. Below, we detail 7 characteristics that the most effective platforms possess.
Whether you call it flexibility, adaptability, or quickness to recover, agility is essentially a company’s preparedness to roll with—and overcome—the punches. Brands need to be able to proactively plan, manage, and quickly pivot when inevitable market and supply chain fluctuations occur.
Agility is made possible by adopting forward-looking technology like AI, which can significantly increase forecast accuracy. At the heart of it is keeping up with forward-looking consumption metrics that illustrate the present and future—not just the past. With certain platforms, brands can even allow key personnel to input ground-level human insights in real time (new distribution, e.g.), and automatically factor them into AI forecasts. This grants brands the ability to prepare for and respond to everything from an unexpected lift/drop in sales to crisis-level outlier events.
Highly accurate demand forecasts are essential to an effective IBP process because they can produce an incredible domino effect across the supply chain:
Accurate sales and distribution forecasts allow brands to reduce working capital, optimize marketing investments, avoid stockouts, improve cash flow, align operations with the pace of demand, understand demand by region and customer, and optimize lead times around purchasing, manufacturing, and logistics. This can also help sales and marketing teams pivot tactics to drive more ROI.
Accurate inventory forecasts reduce costs associated with working capital, transfers, obsolescence, warehousing and other logistics costs; help manufacturing and procurement teams negotiate better prices, MOQs, and delivery dates with suppliers; and improve negotiations for volume cost breaks for raw materials, components, and finished goods.
In the context of demand planning, actionability refers to data that's dynamic, illuminating a path forward so you can start to move in one direction with a clear, confident vision.
By way of example, ask yourself these straightforward and eminently important questions:
How are you benchmarking past performance?
Do you know what contributes to forecast error?
What’s driving sales?
Having access to a platform that enables you to quickly identify and analyze these answers is the first pillar of actionability. The second is having the technology—artificial intelligence—that can identify baseline as well as dynamic relationships between various datasets and time horizons related to your business.
Effective automation simplifies the complicated and streamlines the complex. It's a step-killer—a capability that can transform a multi-layered process into one while slashing hours from the manual process of culling, organizing, and analyzing data. Automation means no more tedious, manual number-crunching. When forecasts are built with unified data across all departments, automation means faster alignment and fewer silos, giving people back precious time.
Typically, it would take hours of sifting through spreadsheets to analyze the factors that contributed to forecast error and how much they impacted the performance gap (actuals vs. forecast). Automation does the heavy lifting for you, so to speak, helping you turn your attention to other priorities.
Artificial intelligence can sometimes feel like a buzzword, but essentially, it’s a series of specialized algorithms that identify dynamic relationships across datasets and time horizons, faster and more effectively than a human ever could. The more models run, the more accurate they can become. There's a common misconception that integrating AI into existing systems would be long-winded and disruptive, but it can be implemented in a matter of months and work seamlessly with the systems and the people already in place.
For an IBP process to be streamlined, collaborative, and forward-looking, it has to leverage AI. And yet, AI doesn’t know everything—it’s not human intelligence with boots on the ground. That’s why when AI combines forces with human intelligence, its dynamic computation lays the perfect foundation for teams to interpret AI’s insights and subsequently make decisions. Even better? Software that enables those human insights to be factored into the AI forecasts.
Alignment means nearly universal cross-departmental visibility that puts everybody on the same page. Instead of your teams tackling informational silos, real-time data links across the company can result in higher forecast accuracy, unified decision-making, and better performance.
When various teams have access to the same cross-departmental data, silos crumble and make way for dynamic decision-making. For example, a sales team may sell into 1,000 more doors than planned for. Or, on the trade marketing front, a retailer may approve, at the last-minute, a shipper display for a particular product. In both instances, these unexpected changes are vital for all teams—supply, financial, sales, logistics, operations, and more—to see and act on. Improved alignment means improved efficiencies across the board.
Accountability is the gap between the effectiveness of a brand’s demand forecasting process and the operational execution behind it. Having full transparency into not only what, but also why, something has occurred is key to making strategic shifts in your demand planning process.
The faster a brand can understand the contributing factors and reasoning for a forecasting error, the faster it can implement the changes that will improve efficiencies, margins, and more. What if a PO comes in as expected but fewer units shipped, indicating an error in forecasted sales vs. actuals? Perhaps manufacturing didn’t make enough units, or there was enough inventory but there were shipping issues as logistical operations lagged. Being able to quickly understand responsibility for the error percentage is useful above all.
Adhering to these seven demand planning characteristics will undoubtedly lift your chances of finding continued—or renewed—success for your brand. And because change is a constant, it's absolutely essential to possess the tools that will enable your IBP process to run like a well-oiled machine and help you weather any situation.