Why your demand planning strategy isn’t working

What is demand planning?

Demand planning and forecasting is the process of combining historical sales data, economic conditions, market trends, and seasonality to anticipate future customer demand for your products.

It’s part of what serves as the backbone for efficient inventory management and warehouse operations.

Effective demand planning allows you to maintain proper inventory levels, better allocate supply chain resources, mitigate risk, and manage supplier relationships.

Thing is, a lot of companies fall short when optimizing this process, often due to siloed data and software tools.

There are a lot of problems that can arise from manual, spreadsheet-heavy demand forecasting workflows.

The problems we see inventory managers struggling with most often with regards to demand forecasting and planning are:

• The inability to adapt to supply chain disruptions.
• Inaccurate or unavailable data.
• Whiplash from fluctuating consumer demand.
• Not documenting processes effectively.

Below, we’ll break down each of these problems and how you can remedy them through more connected software tools and better data.

You can’t adapt to supply chain disruptions…

Historical data can be great, but should only be one part of the equation when forecasting demand.

It can tell you a ton about your inventory and supply chain performance—acknowledging inventory days on hand, burndown, backorders, and the rate of success and timing of shipping and freight.

What can get lost within that, however, are unpredictable market and economic factors.

Shortages, pandemics, recessions… There are many demand planning disruptions that can arise when you least suspect them, sometimes having no comparable event from the past that to draw from.

​​To act quickly and effectively on occurrences like this, you need more nuanced data.

The key here: Give yourself access to real-time analytics and supply chain data.

With active visibility into your 3PL data, transportation data, vendor scorecards, inventory levels, and so on, you’ll be able to pivot supply chain efforts more reflexively and incrementally.

Demand forecasting software tools help you gain access to real-time visibility into any part of your supply chain via always-updating data.

Some popular examples include NetSuite, Oracle Demantra, SAP Integrated Business Planning, Anaplan, Kinaxis, and Blue Yonder. 

Small or medium-sized businesses might also turn to SAFIO Solutions, Garvis, StockIQ, Inventory Planner, and Avercast, though there are many to choose from.

Your data is inaccurate or unavailable…

Manual workflows and siloed data remain the two biggest detractors to supply chain efficiency today.

Are you still reliant on manual, spreadsheet-based demand forecasting methods? 

If so, that can lead to a few different problems with relation to data accuracy and availability.

‍1. Because of human error, your data will be hard to trust.

This is fairly straightforward. If you’re relying on manual processes to log, manage, and analyze your customer behavior and inventory data, chances are there is going to be some human error along the way.

You can analyze that data to gain insights and forecast demand, but overall, your confidence level may not be high regarding those insights.

2. You might need data/engineering teams to access your data.

Perhaps you don’t maintain shared systems across the supply chain, or across teams internally. 

Without centralized tooling, all of the information you need to forecast future demand might be beholden to one team in your org—data or engineering, most typically.

Not only is this data siloed, but it will be more difficult, not to mention time-consuming, for you to access and act on when needed.

3. Your data sharing processes will not be standardized.

While many teams have difficulty accessing needed data, there are also common issues that arise when using that data.

The biggest culprit here is usually data sharing and standardization.

It’s still very common for inventory teams to share and gather data from different partners via different sources, in different formats, and on varying timelines.

Because of that, your data sharing processes with transportation vendors, 3PLs, stores, and so on, will not be standardized. 

It will be inconsistent and difficult to wade through when forecasting demand, and creates a bevy of additional manual work to simply understand the data itself.

The key here: Automate the process of sharing information.

Whether you’re taking in information from your partners or alerting them of new stock levels, new expectations or protocols, and so on, you should seek to automate as much of the process as possible.

With all of your data and demand management processes centralized and automated, forecasting won’t feel as slow or unreliable.

Many of the demand forecasting software tools mentioned above, as well as other workflow tools like Parabola, offer the ability to centralize your inventory and supply chain data in a way that makes it accessible and easy to manage for any internal team.

Fluctuating consumer demand is creating whiplash…

Customer demand fluctuates for many reasons—some clear, some not-so-clear.

For one, there are always natural seasonal fluctuations. Other world or local events will also spring up, of varying levels of predictability, with varying levels of impact on consumer demand.

This also goes back to having real-time data on-hand.

Sometimes, it’s not entirely clear why certain demand fluctuations occur—and in these cases, historical data is not going to serve you much benefit.

Without real-time consumer behavior and inventory data, you’ll always remain a step behind, which could lead to a whiplash effect, where you’re continually reacting to fluctuating demand, potentially over or under-compensating with each fluctuation.

Demand forecasting tools offer a safeguard for uncertainty, and allow you to carry out more sophisticated data modeling.

Real-time, steady data allows you to understand how your customers operate during specific fluctuations, and forecast more incrementally so that you’re adjusting in real-time to less-predictable demand waves.

It’s also important to communicate consistently with suppliers and customers and track what you’re hearing in those conversations back to real-time performance data.

Look at manufacturing and procurement, challenges and timing of obtaining and delivering certain products.

You’re not documenting your processes (effectively)...

Another reason why your demand planning process might not be working is because you’re not documenting your processes effectively (or at all).

Documenting the entire demand planning and forecasting process allows you to be much more agile in response to demand changes.

It brings clarity and consistency to demand management, and will help your whole team work more efficiently.

For example, you’ll be able to stock and manage inventory much better if your procurement manager has visibility into the entire demand planning process.

With transparency across the entire process, you’ll be able to continually improve and understand exactly where there might be hang-ups in your demand planning.

The right software tools help you do this.

With Parabola, for example, you can both document and automate the demand planning process, helping centralize and organize all of your workflows for teams across the supply chain.

You can automate a range of inventory reports, and centralize that information into shared dashboards, that give you and the rest of your supply chain managers immediate access to pertinent data.

The fact is, demand planning and forecasting decisions are only as good as the data used to make them.

If you’re not invested in the right software to back your demand planning methods, you’re likely going to run into one or more of the problems mentioned above.

If that’s the case for you, your next demand planning step should be to audit your software support and see where you can make improvements to automate and centralize your workflows across teams.