Consumer packaged goods (CPG) companies can’t seem to catch a break. Market volatility is rocking the C-suite and front lines alike, and the only thing that’s stable anymore is supply and demand instability. The team at McKinsey & Co. hit the nail on the head when they said, “existing planning capabilities won’t be sufficient for [CPG] organizations to keep pace over the next decade.” Existing planning techniques aren’t sufficient today.
McKinsey analysts are advocating for “an end-to-end transformation of planning.” And while many things must change in the planning process if we’re going to get past these prolonged inventory shortages, the biggest change that must occur within CPG companies right now centers on demand forecasting.
Many CPG leaders say they’re confident that ripping and replacing forecasting and planning systems with newer and shinier versions will provide them with more accurate insights about inventory throughput or customer demand. Yet the biggest mistake CPG leaders can make right now is optimizing internal systems with the belief that this sole action will improve inventory performance and “on time, in full” (OTIF) service levels. You can’t drive consumer satisfaction higher simply by upgrading your technology platforms. Using new tools to do things the same old way leaves you exactly where you were yesterday: unable to sense, much less get ahead of, demand shifts. You’ll still struggle to produce and stock enough goods or the right SKUs.
So, if you’ve started down this path of technology modernization to improve your planning capabilities, make sure you’re also:
Reframing your reality. Inventory-related decisions must be based on more recent and relevant data, not speculation. In this climate, long-term forecasts won’t necessarily help resolve current supply and demand imbalances. Future success will become more dependent on near-term demand sensing capabilities — which was not something widely adopted even two years ago. But it has become abundantly clear that relying on historical demand trends that anticipate demand patterns for six, 12, or even 18 months from now will leave you either over or understocked today. Last year’s summer holiday season will not look the same this year. In fact, you may see seasonal demand start and end earlier than it has before or extend far past its typical expiration date.
Digging into your data from a different lens. With more companies facing unprecedented supply chain challenges and experimenting with omnichannel options, CPG leaders need to look beyond the typical historical trends. Again, celebratory events such as Thanksgiving or New Year’s might still be a core demand driver for CPG inventory. But a sudden inflation hike, stimulus payout, or unexpected tax bill might dictate spending limits. Consumers may seek out a different quality or quantity of goods than before.
Scrutinizing your entire way of doing things. Legacy systems and forecasting models don’t work in a world where something new is disrupting the supply chain every day. Factoring in consumer spend patterns from a year ago without accounting for data anomalies, changing consumer patterns, and new demand signals will severely skew future forecasts. Whether or not you replace back-end planning systems, you must re-evaluate back-end processes and take a new, connected approach across all functions that plan or influence demand — one that facilitates a continuous and timely feedback loop based on a single, unified demand forecast.
Embrace artificial intelligence (AI) and machine learning (ML) technologies. AI and ML are paving the way for companies to model large volumes of data in a scalable way that enables external leading indicators — not only historical data — to drive demand-informed business decisions. The goal is to simultaneously solve real business problems and mitigate new ones, so it becomes easier to meet customer — and consumer — demands over time. However, I don’t have to tell you how hard it can be for humans to identify and make sense of all the demand drivers, especially at the speed necessary for today’s expectations.
In other words, you do need to invest in new technology to improve your planning capabilities. But it must be technology that enables you to approach planning completely differently than you have before, not simply an “upgrade” of the same planning systems you have had for the past decade.
Look for an intelligent software platform that can look beyond the past and sense what’s happening in the here and now. It’s even better if you can find an AI platform that understands the drivers for current demand, can foresee new shifts, and can explain why historical demand patterns may or may not repeat themselves.
The only way we’re going to get past these inventory shortages is if we can accurately predict demand. And we can only do that if we’re feeding our planning systems (new or old) with the right insights derived from algorithms that can anticipate demand. A planning system is only as intelligent as its demand forecast. So if you only make one change to inventory planning, change the way you approach planning. Then, find an intelligent technology solution that can fully support that approach.
David Kane is senior director of supply chain solutions strategy at antuit.ai, a Zebra Technologies company.
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