The biggest shift for me in dealing with the e-Commerce channel was a mindset. I had approached planning for this channel with the same tools and perspective that had worked for me in planning for retail and distribution customers. These were not effective for this channel.
So I had to change my approach and look at using different tools.
I found that it also requires training salespeople to think differently about planning their online business, as it requires a more agile, hands-on approach to planning. Here I outline some of the key differences and also present some ideas for managing demand planning for this channel.
Who’s My Customer?: Unlike the more familiar retail and distribution channels, where demand is linked to a specific customer or location, in e-Commerce the customer is often not clearly defined. Online ordering masks the customer’s identity and location, making it difficult to see how your products are perceived in the market or where the sales are occurring.
Lumpy & Volatile Demand: In addition, demand is often quite lumpy, and changes in how items are managed and promoted can cause demand to fluctuate wildly. And then there is the issue of hoarding, where customers buy large quantities of a product to restrict availability and control pricing. And the explosive growth of sales for some e-tailers is an additional challenge.
Data? What Data?: Another challenge is that in many cases there is limited historical data available to assist with planning. And even if there is data available, it is often of limited usefulness. For example, historical POS data for online sales can be significantly impacted by any or all of the following:
- New listing / De-listing
- Flash sales
- Customer comments (good and bad)
- Availability of competing products
All of these distort the historical data and require significant time to properly analyze how to adjust for these activities.
What forecast?: Another challenge I face in dealing with customers in this channel is getting good forecasts. Some e-tailers do provide forecasts to their suppliers, but the assumptions and algorithms that go into compiling these forecasts are often not clear, and often don’t clearly reflect the impact of past historical events such as promotions or new listings and de-listings. In addition, it’s often difficult to find out what products might be competing with your own products without spending significant amounts of time online comparing the products that are suggested alongside your products. And tracking potential lost sales also requires significant time to analyze correctly.
Supply challenges: There are also challenges for the supply side of this business, as lumpy demand makes planning production and supply quite difficult. Calculating minimum stocking quantities and safety stocks is often difficult and can lead to significant inventory costs if done incorrectly or not managed and maintained. Long lead times will add to the difficulty, as quickly re-stocking high-velocity items can be challenging and potentially quite expensive.
Structure: We found that the structure we had for our brick-and mortar business was not effective in dealing with the e-Commerce channel. We couldn’t simply add managing the online business to the workload of a planner who was also handling brick and-mortar customers. Since the online channels required a different approach and different tools, we set up a separate sales and demand planning team for the e-Commerce customers. This allowed the e-Commerce team to focus on this unique channel and develop the tools and processes that were most appropriate to this channel.
So Why Bother?
With what I have written so far, you may be wondering why any company would try to plan demand for their online business. And I would not blame you for feeling this way. But let’s finish by looking at some of the practices that can make your demand planning for this channel more effective.
Mind Your Own Business First
When I first started managing demand for our online customers, I focused on how these customers ran their business. I analyzed their shipments and sales and tried to anticipate the demand. Since the demand varied wildly, I was often quite wrong in my estimates. I found a better approach was to manage my side of business first, and then adapt it to what I knew of my customer’s needs. Here are my examples of how I approached some of the issues listed earlier in this article.
Managing Lumpy & Volatile Demand
My solution here was first to stratify my items so that I focused first on the items that were most important to the business. In one case there were 12 items that generated almost 80% of the total annual volume for one customer. By improving the forecasts for these 12 items, I would be supporting the majority of the expected demand and any potential sales growth. And I also noticed that there were many items that generated only small volumes over an entire year. While these also needed attention, improving the forecasts on
these items would add little value to the business. Next I assigned all e-Commerce skus to a forecasting model that was reasonably accurate over the available history of the items. I use a 4-month weighted average of shipments as my default model, and I compare this to the sales for the same period last year.
I know it won’t be accurate for all the items, but it gives me a point of reference for comparison. Each month I compare the model forecast to the actual demand and adjust where necessary. And knowing that demand in this channel can vary wildly, I’m willing to tolerate a high bias in any single period. But when the bias remains high (> 30%) over 3 consecutive periods, I know it’s time to re-evaluate the model for the item.
Managing Data By Building Your Own
Since many e-Commerce customers didn’t have reliable POS or inventory data available, I built my own database. I started with the shipment data available from our own system and plotted the annual demand for all the items together to get a high-level view of the overall business. It also showed me where there was seasonality.
Then I broke this data down by individual item volume, and then grouped these into subcategories, such as top items, highly promoted items, highly seasonal items and onetime promotional items. This allowed me to tailor my forecast model selection to each item. It’s not perfect, but better than having no data at all.
Managing The Supply Side
I used the database that I built to help manage the supply side of this business. Knowing how demand varies
by month throughout the year allowed us to set minimum stock and safety stock levels by item, which significantly decreased our inventory levels. We also adjusted these based on the lead time to replenish the supply, allowing us to maintain or adjust these levels if the lead times shifted.
Adapting Our Structure
I learned early on that the online channel required a different approach, and a key aspect of this approach was having demand planners and salespeople dedicated to this channel. The challenges of limited historical data,
volatile demand and uncertain forecast modeling require that the planner and salespeople invest significantly more time in managing this channel than would be required in the more predictable distribution and brick-and mortar channels.
With A Realistic Approach You Can Effectively Plan Your eCommerce Business
Effectively planning demand for online customers is challenging – but it can be done. Above all it requires thinking differently about your business and how you can support these customers. My experience shows that despite the volatile demand and often limited historical data, we can develop the tools and processes that will allow us to map and plan demand and adjust our supply to support this growing channel.
And this capability will be all the more important as this channel continues to be a focus for many retailers and continues to grow rapidly. Effective demand planning in this channel requires a unique commitment of resources that will greatly reward the companies willing to make the necessary investment.