eCommerce Forecasting, The Impact of an Inaccurate Forecast
In part one of our forecasting series, we discussed some of the basics of forecasting within the eCommerce industry and the importance of accuracy. So, what happens if a forecast is inaccurate and what are some ways that retailers and brands can avoid this happening?
Why is Accurate eCommerce Sales Forecasting Important?
Understanding why businesses across industries use forecasting and how it helps is a useful place to start when it comes to understanding the impact of inaccuracy, particularly in eCommerce. Informed and intelligent insight into the future is of great benefit to your organization. Along with ensuring robust supply chain management and close and collaborative relationships with third parties, such as a fulfillment BPO, forecasting helps retailers and brands to make better decisions and predict potential issues, along with measuring their impact.
An eCommerce sales forecast can enable retailers and brands to anticipate future sales volumes, taking into account the macro and micro landscapes, to determine likelihood and pivot according to their sales target. As a result of artificial intelligence, clever forecasting software, and big data, forecasting is now easier, more accurate, and more customizable to each industry and vertical than ever before.
Data, logic, and experiential reasoning are all used in forecasting to determine a direction for the future and how your organization will evolve, this ensures the best chance of success. In the event that a forecast proves inaccurate, usually through more or fewer sales than predicted (one is a better outcome, but both can occur), a domino effect will occur throughout the entire supply chain and fulfillment process.
The Knock-On Effect of an Inaccurate Forecast
Miscalculation of Resources
Over-forecasting can mean over-hiring. Meaning that there are trained people on the ground ready to work, but there aren’t enough orders to process. Resulting in a loss of earnings for workers if they are sent home, or a waste of salary for the brand if no work was able to be completed.
With an under-predicted forecast, there is the opposite issue of there not being enough members of staff to complete the orders. This increases the margin for error, with potential late deliveries and rushed packaging.
These results can differ depending on if the brand in question uses in-house resourcing versus the services of a 3PL. But under- or over-forecasting resulting in a miscalculation of resources will affect the brand either way.
Preparing for higher sales that do not come to fruition can result in overstock. For brands hoping to become more sustainable, this is not a good look. Beauty and cosmetics items can expire, while clothing changes with the seasons. Unsold items are often destroyed or sold to companies that sell clothes out of season – a more sustainable option but a loss of income for the brand nonetheless.
Employee and Customer Satisfaction Drops
At our facility, we house multiple well-known brands, and staff will associate themselves with the brand, not the provider. Brand reputation will be affected if disgruntled staff are dismissed early due to a lack of items to process (over-forecast). Equally, if staff are feeling overworked due to more orders than expected (under-forecast). For customers, the impact of an over-forecast could mean that their order is out of stock, and they now won’t receive it on time. While under-forecasting could result in an out-of-stock notification, meaning they will shop elsewhere.
How Brands Benefit from Accuracy in eCommerce Sales Forecasting
Ensuring that the volume of sales is correctly forecast, means that the necessary resources can be organized and adjusted accordingly.
Preparation is key, especially when it comes to peak season – such as Black Friday and Cyber Monday. Brands will often ramp up their sales offerings even weeks before these dates. With the holiday season directly after that, it is in the brands’ best interests to be as prepared as possible.
Examples of Forecasting in eCommerce
Examples of what is being forecast are helpful to better understand e-commerce forecasting, and why it is needed. So, what is most helpful to predict ahead of time, to reach the best outcome for business?
- Calculation of cash flow – timely estimation of your financial needs
- Identifying and estimating recurring costs
- Recognizing new competitors in your industry and estimating their threat
- Analyzing the potential of new products or services
- Using historical sales data to predict future sales growth
- Identifying relationships between variables, such as the cost of advertising versus revenue potential
- The cost of acquiring a customer versus the lifetime value of that customer
- Allocating resources efficiently and budgeting for contingencies
How Frequently Should Brands be Forecasting?
At various times throughout the year, forecasters will look to create short, medium, and long-range forecasts. That said, forecasts made further in advance are more likely to be inaccurate. The chosen method of forecasting must meet the expectation of how the results will be used.
Short-range forecasting happens around three months in advance and works well for anticipating peak season, and big offers and sales.
A medium forecast will usually cover any time from three months to three years. While a long-range forecast is more focused on the strategic level of retail, planning for new products, and other eventualities that suit a longer lead time.
With short-term forecasts, there is a fine line to tread when it comes to maintaining accuracy. There must be enough time to respond to the forecast. So, while allowing enough time for error, preparation and potentially comparing other forecasts, the turnaround needs to be short enough that the estimates remain as predictable as possible.
Are There Any Limits to eCommerce Forecasting?
Forecasting is essentially and most simply, an attempt to predict the future. Although it involves a great deal of research, informed by data and logic, the future can still be unpredictable. So even when the data used is high quality, it is necessary to rely on a mix of new and historical data. As things are constantly changing, that historical data can sometimes prove unreliable.
Within eCommerce, forecasts serve a great purpose and help immensely with planning and predicting. Therefore, accuracy is key to minimizing these limitations.
Potential Limits to an Inaccurate Forecast:
- Incorrect information supplied by experts
- Inaccurate historical numbers
- A sudden or unexpected change in market conditions
- New industry regulations
- Crisis or natural disaster – impossible to predict
Key Takeaways, eCommerce Forecasting Needs to be:
- Accurate – Ensure thorough research, plan in place in case of error, easily comparable to alternate forecasts
- Timely – Ensure you leave enough time for necessary changes, without being so far out the forecast becomes inaccurate
- Resolute – The forecast must produce the same results every time. By doing so, users will be confident that the system in place is reliable.
- Uncomplicated – The forecast should cover all bases, whilst still being easy enough for all users to gain understanding swiftly
By being aware of the limitations of forecasting, having a good knowledge of the types of forecasting and the benefits of each, and an understanding of the time scale required for the best results – it will be easy to achieve accuracy and avoid the dreaded results of an inaccurate forecast.