A Day In the Life - Demand Planner
Dave is a senior demand planner at ACME Drink, a fast-growing functional beverage brand. He wakes up to an email from a VP:
"Amazing news! We just closed our biggest retailer yet – Bullseye Markets. They want our top 5 SKUs in 100 West Coast locations starting next month. Need your demand plan by Friday for the exec review."
It’s great news for the business, but a tough job for Dave, who is responsible for (and paid on) keeping forecast accuracy above 80% at the product family level.
THE OLD WAY: A WEEK OF FORECAST THRASHING
Monday:
Dave opens his demand forecasting software and stares at his screen. They’ve been using a particular time series seasonality model from the planning system for the past year. It does a reasonable job (even though it doesn’t forecast at the SKU/DC level). But Bullseye feels like a completely different animal. Will this model still work? Dave knows five other forecasting models are available in their demand planning software - would any of them be better?
Bullseye is much bigger and more complex than ACME’s current retailers, and every point of accuracy matters. So Dave spends the day evaluating the pros and cons of the different models.
Tuesday:
He begins the next day by picking one model and forecasting the Energy Berry product family. The results are decent!
But Dave knows the VP of Supply Chain will ask: “Sure, but what’s the breakdown between Energy Berry singles vs 4-packs vs twelve-packs for the Bullseyes in the greater LA Basin area?”
No matter which model Dave uses, no matter how much manual tuning he attempts, his forecast accuracy plummets at the SKU level.
Wednesday:
Even after pulling more historical data and PoS data from comparable retailers – and running a different set of models on this data – Dave never develops a forecast that gives him confidence at the SKU-and-Location level
By the end of the day, he admits that a regional product-family forecast is the only thing that can be workable by Friday. Given the unknowns around Bullseye, ACME will probably wind up carrying excess inventory for months while learning this new market.
Thursday:
Dave is close to pulling something together when he gets another cheery call from Sales: “Bullseye wants to go Nation-wide!! And we got them to agree to stock all our SKUs, not just the top 5”
With all of his prior work scrapped, Dave begins the re-planing process. He runs all his models again with updated assumptions about cannibalization (between SKUs, and with other retailers), East Coast seasonal patterns, and a dozen other foundational changes.
The exec review gets pushed back by a week. Dave is under pressure the whole time.
The following Friday: Dave reverts back to a family-level forecast with a long list of caveats and assumptions. The exec team makes the decision to simply add extra inventory at a large number of DCs to ensure the launch with Bullseye goes smoothly. Despite the booming popularity of ACME Drink, there’s a palpable frustration at the inefficient use of capital.
THE OMNIFOLD WAY: FROM CHAOS TO CLARITY
With Omnifold, Dave is done by Monday afternoon. How?
One-click forecasting. He starts by loading a data file with the West Coast Bullseye locations, types in “Top 5 SKUs only” and hits “Plan”. No model selection needed – Omnifold has trained one self-improving forecasting model, and it consistently outperforms any other system.
Purpose-built for ACME’s supply chain. All of the complexities of ACME’s operations, such as the mapping of “Which SKUs are available at each distribution center?” and “Which distribution centers are associated with which retailers?” were autonomously learned by Omnifold during its training process. Even though Dave knew these assignments, before Omnifold there was no way for his demand forecasting software to understand them, let alone model the cascading impact of a big change like signing Bullseye.
Gets smarter, faster. As a seasoned Omnifold user, Dave knows that the system can take any type of data he throws at it – sales plans and other CRM data, marketing spend, detailed promotion calendars, and even the notes from his calls with Bullseye and other customers. For this forecast, Dave realizes that Omnifold could be even more accurate in its predictions if it had access to other Bullseye launches in the past. He finds third party data on other beverages sold at Bullseye, uploads the data, and then lets Omnifold do the complex math of figuring out the correlations and optimizations.
Accuracy all the way down. Omnifold is designed for forecasting at maximum granularity. Dave’s demand plans show the breakout by flavor, pack size, distribution center and location…it’s everything the S&OP team could want, and more.
Instant Replanning: When Sales calls on Thursday, Dave simply types into Omnifold: "Add in all US Bullseye stores, and plan for all our SKUs." Omnifold instantly updates the forecast again, including the nuances of East Coast preferences by city and significantly more complex cannibalization dynamics.
THE RESULT: AGILITY, ACCURACY, CAPITAL EFFICIENCY
ACME’s S&OP cycle shortens dramatically with Omnifold instantly planning and constantly re-planning to adapt to new situations. But the benefits of cutting-edge AI for supply chain go far beyond time savings.
Accurate forecasts enable ACME to expedite fewer shipments while carrying cutting inventory by a full week, unlocking significant cash flow. The freed-up capital funds a 15% increase to ACME’s marketing budget (with intelligent allocations also powered by Omnifold).
Freed from endless replanning cycles, Dave has several hours a week to drive critical strategic discussions, which ACME had never found the time to prioritize:
What SKUs are under performing? How much are they dragging down margins? Should we discontinue them?
Would adding a new distribution center help lower shipping costs, improving cash flow?
How could we work more closely with marketing to optimize the impact of promotions?
Before Omnifold, Dave felt like a bottleneck on ACME’s growth – struggling to find the least bad option for the operations team. With Omnifold, he helps the planning function scale with ACME’s surging growth.