Using an ERP? Here’s How to Scale Your Demand Planning and S&OP Process
Whether you use SAP, NetSuite, CIN7, Katana, DEAR Systems, Fishbowl, a Microsoft ERP, or another tool, chances are it’s time to ditch the spreadsheets and adopt a more scalable demand planning solution — which integrates with your ERP.
By Sophie Guimaraes, Kunal Kohli & Jonathan Zalman | May 14, 2021
In this article we examine…
- How CPG brands can scale their demand planning process and S&OP meetings.
- The impact and importance of automating your supply chain processes, such as using an ERP for operations or an AI platform for demand planning and forecasting.
- Why brands should adopt an independent demand planning solution that can “sit on top of” and augment their ERPs.
- Why most demand planning tools are typically too rudimentary for the needs of today’s complex supply chain challenges and ever-changing consumer behaviors.
- Why AI is the primary choice for finding relationships and patterns among complex datasets, plus how AI can be augmented with human intelligence.
Introduction: ERP, easy as 1–2–3
Whether you’re a rapidly growing brand with a surging presence or you’ve already got hundreds of SKUs available at retailers nationwide, you know that using an ERP is vital to managing and scaling your operations. A majority of CPG brands have turned away from spreadsheets and adopted an ERP to improve their orders and inventory management, become EDI compliant, and manage their accounting and financials. Plain and simple, ERPs make life easier — and adopting one is a clear sign of success.
In other words, adopting an ERP isn’t a starting point — it’s a growth milestone.
But many brands do not take the same approach they do with an ERP to scale their demand planning and forecasting, which is puzzling. Why continue to rely on spreadsheets to continually execute one of your most essential processes?
So you’ve ditched spreadsheets for an ERP. Now leave the manual forecasting methods behind, too.
If they’re leveling up elsewhere, then why do so many brands continue to rely on spreadsheets for their demand planning needs? Maybe it’s about comfort with a “tried-and-true” approach, a belief that spreadsheets are working “well enough.” Maybe it’s about onboarding, adopting a new system, or relying on computers to learn (from) the nuances of your business. For one reason or another, the logic does not track, and brands are paying the price for it.
But contrary to popular belief among CPG-ers, an ERP is not a one-size-fits-all solution, with one exception being its forecasting capabilities. In that sense, it falls on the shoulders of brands to level up their demand planning solution just as they have with their supply chain operations — through automation.
Why Certain Demand Planning Methods Fall Short
1. Spreadsheets are not scalable
Just as ERPs automate and centralize key operational and financial processes, the best demand planning solutions generate similar efficiencies. And as your company grows, so too does your data: 20 SKUs swells to 50, plus a new category. Local distribution becomes regional which in turn becomes nationwide. You’ve gone from 5 customers to 50 and are dealing with multiple distribution centers. The list goes on… and remember, these are good growing pains!
As the data piles up, the complexities of demand planning grow as well. At a certain point, processing sales orders and managing inventory using spreadsheets is simply too slow, too siloed, and unscalable. As a result, the need for better forecasting infrastructure becomes ever-pressing. But spreadsheets are not built to generate the kind of efficiencies that help brands scale:
- Whereas spreadsheets rely on slow, manual processes to get the job done, automation is all about generating speed at scale.
- Spreadsheets often lead to silos, as various teams may come to the supply chain planning table with their own view of the business. During the S&OP process, sales may present a spreadsheet that shows their own understanding of future demand.
- Manufacturing and supply teams may have their own process and logic; the same goes for finance teams, and so on. This can lead to misalignment, wasted time, operational silos, and increased working capital costs.
- Spreadsheets lack the kind of machine-learning capabilities that can identify dynamic relationships and patterns that consistently raise accuracy levels, generate actionable insights, and increase efficiencies.
2. Forecasting With the Wrong Tools
ERPs aren’t typically built for the kind of sophisticated, modern forecasting solutions that CPG brands need to keep pace with, and get ahead of, demand. While ERPs are great for managing your supply chain operations, there are a number of demand forecasting potential pitfalls you should be aware, including the following areas where ERPs fall short:
- One-dimensional linear regression models that only analyze historical sales
- Lack of granularity, especially down to the ship-from, ship-to, and SKU levels
- Inability to keep up with the business at a constant pace, whether that pace results in hypergrowth or stems from multi-channels and supply chain disruptions
- Strictly a business intelligence (BI) tool without any AI to pick up on and calculate trends and patterns across data sets
- Inability to unite human and artificial intelligence to reflect distribution changes, last-minute promotions, and supply constraints in AI forecasts
- No lock-in periods or supply chain lead times taken into consideration
- Lack of full automation
- Accuracy levels falling short
- Silos and lack of visibility across all departments, despite the ERP’s best efforts
Sound familiar? It’s what drove our founder to start Unioncrate, after all. But there’s a silver lining: an opportunity is created to adopt an independent demand planning solution that can sit on top of your ERP and level up your demand planning process.
How to Level Up Your Demand Forecasting & S&OP Process
1. Gain visibility, simplicity, and granularity — via automation
Granularity is key to understanding a full picture of demand. Forecasts broken down by SKU, ship-to, and ship-from help you better understand your business as a whole. And when this information is unified and available across the entire company, departments shift from operating in silos to working together cross-functionally.
With this level of understanding, demand planners can optimize key cost centers, align forecasts with purchasing and manufacturing plans, and optimize logistics, working capital, margins, and more. It’s even better if it’s all automated, which saves time — lots of it. Most CPG brands with ERPs are likely still using spreadsheets to do their forecasting, after all.
2. Get accurate, really accurate, and reap the rewards
With that granularity comes the ability to reach newfound heights of accuracy, an incredible money- and time-saving asset for CPG brands. The domino effect of high-accuracy forecasts can be felt across the supply chain and business at large. Among the benefits of accurate sales and distribution forecasts are:
- Better discussions and negotiations with distributors
- Reduced/optimized working capital, including warehousing and labor costs
- Optimized marketing investments
- Fewer stockouts
- Improved cash flow
- Optimized lead times and DC splits
- Reduced COGs and increased margins, plus improved negotiations for volume cost breaks for raw materials, components, and finished goods
- Greater ability for distribution teams to help sales teams
- Increased visibility for sales teams into customer inventory levels, allowing them to incrementally upsell the buying and planning teams
3. Get AI-driven insights and forecasts
Between good, clean data and commercial benefits lies the process of understanding how data translates into dynamic insights about your supply chain, business model, and the CPG industry at large. In order to open the “black box” on demand and eliminate blind spots, it’s vital to be able to reveal the factors influencing past and predicted sales. This is the job of artificial intelligence that’s trained inside and out on the nuances of the consumer goods industry: to analyze data and find dynamic relationships between datasets across various time horizons — quickly.
A business’s demand sensing capabilities should be versatile and ever-aware. Luckily, AI is never static. Its algorithms are trained to tell us something we don’t know (due to either time or capability constraints, for example) by powering through a jungle of complex data with every passing millisecond. Even better, since AI “learns” as would a human brain (hence the “intelligence” in “artificial intelligence”), it’s self-correcting or self-learning, so to speak, and can increase in accuracy every time it runs while yielding dynamic data-driven insights.
4. Get agile and collaborative — across teams and between HI and AI
Powerful, precise, and agile as it may be, AI does not know everything. The key to fully integrated agility is collaboration — specifically between artificial and human intelligence. How could it be? One-off circumstances pop up in the real world that AI, without human input, doesn’t have insight into, such as a last-minute shipper approval.
Combining AI and HI (human intelligence) allows you to unite AI forecasts with sudden events that happen in real time, which can look like anything from new distribution gains and upcoming promotional activity to one-time orders from a specific retailer. A key element of agility is integrated data and processes, which prevent your team members from working in silos.
Uniting the forces of AI and HI permits team members to share information only they may be privy to. Balancing data with boots on the ground enables the kind of quick pivots you need to make to optimize production. This results in company-wide visibility and alignment among decision-makers, enabling the kind of rapid reactivity needed to face supply chain occurrences head-on.
The Benefits of Automation on the S&OP Process
When demand forecasts are automated and sales data is visible across an organization, S&OP meetings can begin from a place of alignment rather than difference. Here are some ways automation can benefit the S&OP process:
1. Increased efficiencies.
S&OP is a melding of the minds: Multiple stakeholders from various departments come to the table to align on a demand forecast. But data between business units can be varied or siloed. With an automated demand planning process, brand data is universal and agnostic. There is one single source of truth. This makes cross-functional team dynamics stronger and more efficient, pushing the decision-making process in the right direction, faster.
2. End-to-end supply chain visibility.
Having a complete picture of sales and inventory data is essential for creating a demand forecast. Automation enables that.
3. Refocused sales teams and increased employee efficiency.
Less time spent on demand planning-related tasks frees up staff to put their energies into other growth efforts, enabling sales teams to focus on growing the business rather than spending their time manually tabulating forecasts.
4. Increased assurance during uncertain times.
When key stakeholders can trust demand forecasts, they can confidently allocate resources in areas that would maximize profits and operational efficiencies, such as investment in products with higher profit margins.
5. Economies of scale.
Among other benefits, forecast accuracy helps brands prepare to take advantage of new sales opportunities. As companies scale, profits should increase relative to increases in sales volume. The larger the output, the lesser the costs. Meanwhile, supply, R&D, and distribution costs will decrease per unit sold, while profit margins increase.
It bears repeating: If you’ve leveled up your operational processes with an ERP, the same logic applies to brands who continue to rely on spreadsheets for their demand planning needs. It is the first step to achieving something greater: scalable growth. And the sky’s the limit.
Unioncrate is an AI-powered Integrated Business Planning (IBP) platform that delivers demand forecasts with unmatched accuracy, collaborative visibility, and actionable intelligence — enabling CPG brands to plan and execute agile supply chain strategies at the click of a button.