For a multichannel B2B client with sales of $150 million annually doing ecommerce and wholesale, we performed an operational assessment to determine how it could make its two East coast facilities more efficient.
The business has an average order value over $400 and about nine packages shipped per order. The strategic plan was to add a West coast facility and select a new ERP to replace its 20-year-old legacy system.
The company has effective cost controls and expense reporting. Its controller produces an elaborate historical management report summarizing transactions, AOV and fulfillment expenses, called the “green book.” While the company has years of data, analysis did not reveal actionable areas to investigate and improve. One of the longer-term objectives is to detail report work by department and employee when the new ERP is installed.
This is how we helped this B2B company research and establish initial benchmarks to measure fulfillment center productivity, and the process steps used to collect and analyze the initial data:
Metrics to Analyze
Establish study group
The study group was made up of the CEO and vice president of operations to select and implementing metrics; the controller to summarize expenses and hours worked from payroll; and an IT/analytics person to understand data availability and sources and prepare the new analysis.
Measurements
We initially focused on 14 fulfillment metrics every ecommerce company should monitor, as outlined in a previous blog post. If you’re starting to measure ecommerce productivity, this is a good place to start. Once you have these in place you can drill down to find ways to increase productivity with new procedures, processes and layout.
The chart below shows some of the basic differences in the level of detail between the existing management analysis (green book) and the new analysis to be developed (red book).
Data Comparison: Two Analytical Approaches
| Factor | Green Book | Red Book |
|---|---|---|
| Total fulfillment costs (incl freight, profit sharing, benefits, taxes) |
x
|
x
|
| Total fulfillment costs (excluding the above) |
x
|
|
| Direct labor (payroll and hours) |
x
|
|
| Indirect labor (payroll and hours) |
x
|
|
| Facilities costs |
x
|
|
| Packing materials costs |
x
|
|
| Cartons shipped and average fulfillment cost per shipped carton |
x
|
x
|
| Order profile analysis |
x
|
|
| Other costs |
x
|
|
| Total cost per order |
x
|
x
|
| Cost per order by expense category |
x
|
Map Expense Data to Analysis
In the prior blog we defined what expense centers in the P&L statement should be included in each metric. The controller then mapped the data from the expense system to the new analysis. For example, the facilities expense category was made up of lease costs, utilities and amortization/depreciation of material handling equipment.
Start by looking at 12 months of data. When you’re confident of the accuracy and have the reporting in place, move to quarterly and monthly reporting. This client restated three years’ worth of expenses by month to the new format, which gave them high-level trends to review.
In the earlier blog many of the metrics use total fulfillment expenses to calculate cost per order and cost per carton shipped. The new analysis calculates total fulfillment costs two ways. The existing analysis included freight expenses and benefits including profit-sharing, health care and payroll taxes. This obstructed the more direct costs in fulfillment.
The new analysis calculates and graphs cost per order and cost per shipped carton both ways. Our rationale is that these expenses vary widely between companies, if comparison is ever desired.
Red Book Highlights
Space doesn’t allow for all the benefits from this case study. Here are a few financial observations that were part of an initial analysis outcome as the operational assessment continued.
Cost per order: Total fulfillment costs with freight, profit sharing, benefits and taxes had increased 30% in three years. When they were excluded the cost rose 25% in that period. This gives an improved focus on where to concentrate operational assessment activities.
Labor: For the first time, management of the B2B company calculated direct and indirect payroll expenses and hours worked for all fulfillment activities. When freight, profit sharing, benefits and taxes were excluded, direct labor is 68% and indirect labor is 11.8% of total costs.
Freight costs: When all expenses including freight, profit sharing, benefits and taxes are considered, freight expenses are 28.1%. Most orders are shipped LTL. By contrast, an ecommerce business using small parcel might find its total freight costs are larger than all the other fulfillment expenses when excluding profit sharing, benefits and taxes.
Facilities costs: This is a private B2B company and the owner is also the landlord. Total facilities costs are 5.4% of total expenses excluding freight, profit sharing, benefits and taxes. These costs are very low as they are older buildings which have been totally depreciated and the owner receives no rent. If and when the company has to move into newer facilities, the occupancy costs will be 3-4x higher, adding substantial costs to each customer order. This is significant as the company is considering a potential West coast facility.
Profit sharing, benefits and payroll taxes: The total benefit rate is 32%. In the past, this was added to the cost per order analysis which obscured the direct cost.
Order profile: Again, the AOV is over $400 with an average of nine cartons on a shipped order; shipping is typically shipped LTL. The new analysis showed 20% of the orders had less than three items consolidated into one carton, at a value under $50. Additional work is being done to better understand the order profile and ensure that small orders are efficiently picked, packed and shipped.
While this analysis covers a B2B company, in DTC ecommerce companies we often find the reverse scenario in terms of order profiles. Up to 20% of orders may be very large ones which inflates the AOV. A better understanding of order profiles will shed more light on cost per order, hours worked, dunnage and freight.
Future objectives: With the legacy system, detailed productivity data and reporting by department and employee is not possible. There was no easy way to accurately collect transactions and hours worked by department or employee. Where employees are cross trained and work in multiple departments, the time recording system will need to be modified to accurately log hours worked in each department and track the costs.
When combined with the operational analysis of the fulfillment processes and layout, these new approaches to understanding costs will yield areas of investigation for potential cost reductions.
Brian Barry is President of F. Curtis Barry & Company