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The pandemic and the uncertain times after it have taught us that we must work with greater flexibility and be ready to face the unexpected. In the modern world, agility takes precedent over the familiar static planning processes of yesterday. This is where demand planning and sales forecasting come in.
Businesses can save time and energy with financial planning automation, but automation can only go so far and will only follow the instructions that it is given.
It is not enough for you to sit back and let those algorithms run — leaders within your company must update those instructions as often as possible to adjust to market realities.
These instructions gather information automatically and constantly to deliver it in regular reports. Such reports provide information about how things are going. When combined with historical data and typical trends in the industry, businesses can also use them to predict future demand.
That prediction involves two key steps: sales forecasting and demand planning.
What Is Sales Forecasting?
Sales forecasting involves the use of dynamic, rolling forecasts to help businesses adjust as they plan for the future. They leverage gathered data to adjust their current plans to the current market environment.
Rather than a static annual forecast, this method makes it easier for an agile company to adjust its manufacturing and avoid lost revenue. Automated reports free the planners within your company for higher-level tasks — team members spend less time writing the reports and more time acting on them.
Sales forecasting involves a thorough review of a variety of business factors, which include:
- Risk
- Profit
- Working capital
- Inventory
- Labor costs
- Sales expectations
With all that information, businesses can more accurately plan their spending based on expected revenue for a certain time frame and use that prediction to maximize profit.
This system also makes it easier for business leaders to identify problem areas and bottlenecks in the overall structure, which makes it easier to course-correct with a proactive approach rather than adjust after the fact and struggle to catch up with the competition.
Sales forecasting is made possible by revenue forecast models, which predict a number of deals and sales in a given period, be it a month, quarter, or year. This forecasting can also adjust for seasonal changes and increases or decreases in demand as well as be divided by product sold, region of sales, and geographic area.
As a result, you can model revenues for the long term by comparing the forecasted volume of sales against cost.
What Is Demand Planning?
Demand planning takes sales forecasting one step further. It starts with the forecast but goes deeper and dives into the nitty-gritty of business operations to consider the logistics of meeting the hypothetical forecast and ensuring it matches reality.
Modern demand planning accounts for production, distribution, and where to hold inventory to meet the demand that the sales forecast predicted. It also analyzes how you can best leverage capacity, raw materials, and equipment.
Proper demand planning uses the sales forecast to work around spikes and dips in demand based on both historical seasonality and current market trends.
In these uncertain modern times, demand planning requires greater agility — the ability to change direction when supply chain disruption or other problems rear their heads and disrupt normal operations.
Demand planning is the process of planning for forecasted demand while attempting to expect the unexpected at the same time.
In doing so, demand planning helps businesses deliver the greatest efficiency with maximum customer satisfaction for the lowest possible cost — all of which maximizes profits and increases the number of repeat customers.
Demand Planning vs. Forecasting: The Similarities and Differences
These two terms seem very similar, and on the surface, they are. How are they the same, and how are they different?
Similarities Between Sales Forecasting and Demand Planning
Both models are ways we use to plan for future demand and to meet it with the maximum profit possible. They both do their very best to predict the future and prepare the company for it. Both must work together to maximize the number of revenue opportunities for a minimum of fuss.
Your company can’t have demand planning without good sales forecasting because demand planning relies on sales forecasting to act as a foundation for the plan of action.
Differences Between Sales Forecasting and Demand Planning
The primary difference between the two is their place in your overall process — sales forecasting happens first, and demand planning comes after.
Sales forecasting is a hypothetical stage run when a project is first starting. It uses historical data and upcoming trends (based on current data) to predict, or “forecast,” how many sales your company should expect and the demand that it will have to meet when the time comes.
Demand planning is the second stage, where your business must act upon those forecasts. This work involves ensuring that you have the right amount of inventory in the right place or that you can move that inventory to meet changes in demand when the time comes.
It also includes confirmation that your supply chain can deliver replacement products when needed to meet changes in demand and that you have the labor available to do so and the internal infrastructure (both in hardware and software) to make it happen.
Challenges and Consequences
The collation of all of the data necessary to create an accurate forecast is an enormous and difficult task. Large companies with thousands or millions of customers have it the hardest. More customers require more infrastructure, and more infrastructure — and people within it — takes more time to adjust.
But demand can change on a dime, and supply chains and transportation availability can change even faster. Big data helps make it easier to predict those changes, but that data is impossible to navigate without help from advanced technology.
The consequences of failure to navigate that data are dire — and most arise when forecasting is not done correctly. Frequently, bad forecasting comes from limited information rather than a poor understanding of the information — but the results for your operation are the same.
Understock and Lost Revenue
If your business fails to adequately forecast the number of sales it should expect for a particular period or product, it can suffer a significant loss of revenue and reputation.
When customers want to buy an item and can’t because of low availability, they aren’t giving you money and will spend it elsewhere. They may be less likely (or even unable) to buy from you in the future.
One notable recent example is the Playstation 5. Sony still suffers supply issues for its newest console years later, which results in overinflated demand and encourages scalpers. All because the company failed to predict interest at launch and build an inventory to match that interest.
Because many customers who want the console and don’t have one can’t buy games for it, Sony loses revenue on two fronts.
Overstock and Unnecessary Costs
On the other hand, improper sales forecasting that predicts more sales than occur leads to wasted manufacturing and storage costs, which ruins all of the careful work that goes into corporate financial planning.
More products made in anticipation of higher demand mean higher costs for raw materials and labor — and when sales for that larger inventory come in lower than expected, it can result in lower profits or even translate to losses.
That disparity in expected and actual revenue can significantly disrupt future operations since the business has fewer funds to work with than anticipated.
Those costs continue to accrue because the excess inventory incurs storage costs until it’s sold, donated, or recycled into other products, which cuts into revenue further. In the worst-case scenario, demand fades, and your business can’t move the product at all — the inventory sits in storage until you cut your losses.
The firearms industry suffered such a loss after the 2016 election — anticipating the traditional run on weapons and ammunition after the expected Democrat victory, manufacturers produced a huge number of additional products.
The “Trump slump,” created by complacency among firearms owners during the Republican presidency, resulted in a massive surplus of firearms and a significant drop in their cost until the pandemic in 2020.
The Wrong Stock at the Wrong Time
Both of the issues discussed above come from poor sales forecasting. But they aren’t mutually exclusive.
It’s even possible to have both issues in different places thanks to poor demand planning. If your business targets a large geographical region with multiple subdivisions, you must account for higher demand in one area and lower demand in another.
When the two areas have equivalent inventory, the first area suffers a shortage and the latter a surplus.
Great demand planning will move inventory in uneven amounts to accommodate the differences in demand — more in the first area and less in the second.
Good demand planning can make up for the difference with quality logistics planning — the business ensures it can move the product to where they’re needed and meet demand before it cools down.
But this redundancy is not always possible with the information available, and rapid shifts in the supply chain and sudden shortages in shipping availability present unpredictable obstacles.
Because businesses struggle to account for these sudden changes, consumers continue to see intermittent product shortages well after the worst of the pandemic has passed.
When to Forecast Sales
We believe sales forecasting should happen early in the planning process. Whether to prepare for an upcoming quarter or a new product launch, it forms the foundation for the rest of the process. It covers planning, production, release, and post-launch review.
Because of uncertainties in the modern market, sales forecasters should continue to gather data and iterate throughout the chosen period. As the sales forecast changes, so too should the demand planning. The market is never static for long, so while the sales forecast happens first, it must remain an ongoing process.
Fortunately, your business can use automated software to gather information and build reports about sales and changes in them in real-time. These reports can analyze changes in the area, adjustments in demand, and more. You can use this information to see where your forecasts hit the mark — and where they didn’t.
When that happens, you can make adjustments to make the most of your current situation and course-correct for the future.
When to Plan Demand
Demand planning should happen later in the process — after the sales forecast is finished, but before the sales forecasts begin and the product goes to market.
It involves diving into the fine details of business operation and making the best of the resources and infrastructure available. Because of this, it’s typically done by the lower members of management, who act on the plan handed down to them. They also reject or adjust parts of the plan as necessary to meet the demands of reality.
Life is unpredictable, and the business world suffers from the acceleration of unpredictable change the most. Businesses use demand planning to prepare for the ways reality differs from prediction models to drive changes in the forecast and maximize revenue with minimal issues.
FAQs
Forecasting comes first. Plans need a forecast to guide them to specific goals and highlight specific challenges.
Each is a separate part of a three-step process to decide on your company’s financial goals. Sales forecasting and demand planning show you how likely you are to get there.
Your business should use the forecast to guide the plan.
Planning comes first. The budgeting process determines how much you can spend to put the plan into action.
QBIX Analytics: The Best Way to Automate the Data You Need to Forecast and Plan
The best way to build and adjust a sales forecast and put it to good use to plan demand is to gather and leverage information. Unfortunately, human beings can’t navigate the amount of data required to make quality plans in the modern business environment.
Software-as-a-Service (SaaS) systems make it easy for businesses to gather the data they need and put it to work.
QBIX Analytics is one such provider. We offer a variety of valuable tools for data-gathering and provide quality service to help businesses leverage their data.
Contact us today to schedule a 15-minute meeting to see if QBIX is the right partner for your business.