Is it the customers’ product demand schedule or lack of planning foresight that has you in a shipping frenzy?
I spend a fair amount of time at various client companies, often in remote sites and plants in addition to their headquarters. I interview many people in numerous roles during our internal control engagements, internal audit consulting or whatever projects these companies ask us to work on. I also observe many activities, such as inventory receiving and inspection, work in process operations, construction of fixed assets, and how all these are recorded in the sub-ledgers and represented in financial statements.
A while ago I decided to develop an Aged Backlog Report for one client company since they were struggling with meeting customer ship date requests. I divided the report output into 10 columns: 5 future and 5 past. Each backlog item, as documented in sales orders now falls into one of these 10 columns. For example, a customer ordered item requested to be shipped on May 26, 2016, at this time of writing falls in the Next 30 Days column. If not shipped by the due date, it will automatically be moved to the Past 30 Days column and so on. The full range is Over 180 Days in both directions, future and past. I testing I implemented the report at several other client companies.
In the process of developing this report and making it useful I was thinking of a phenomenon so many of the manufacturing companies I work with experience: Uneven distribution of product shipments throughout the month with a peak shipping day on the last day of the month or quarter.
I recently looked at several of these Aged Backlog Reports, all from different organizations, with different product lines and a different customer base each and noticed something very similar in all of them: The customer Requested Ship Dates (due dates on sales orders) were almost uniformly distributed throughout each accounting period.
I didn’t see a concentration of customers requesting their shipments to leave the warehouse on the last day of the month or the last week of the month; yet in all of these companies there seemed to be relatively less shipping activity going on during the month followed by a shipping frenzy toward the end of each accounting period, culminating with an almost epic effort to get as much stuff out as possible before the clock strikes midnight.
This was confirmed by examining sales journals in several accounting periods (assuming billing was not much delayed following actual shipments).
What causes this phenomenon? Or is it really a phenomenon given how common it is? I know for a fact that this is not driven by customer specific demand, as sales orders’ due dates clearly indicate. Is it lack of planning? I don’t think so. Sales orders’ due dates are supposed to create the demand and drive purchasing of material, scheduling of machines and work centers and allocation of resources. If planning is not to blame, then it must be the actual results from these planning activities, or just not adhering to schedules.
Despite all this logic I think it all comes down to natural human behavior. We know that we have an inherent quality to procrastinate; we experience that with daily chores we are assigned to, filing our tax returns, and other activities, when we pretend that there is plenty of time to complete them and one more day won’t make any difference. There may be people exhibiting less, or even none of this behavior but the majority of us are impacted by this on some level.
I think this quality is carried over to the work place. The first few weeks of lighter shipping each month followed by a much more intense week and especially the last two days of the month or the quarter, seem to prove this theory.
Which brings up another question: If companies seem to exhibit such uneven shipping and fulfilment output throughout each accounting period, is that an indication that resources are underutilized? Are people taking their time much of the month, only to accelerate their activities (hence the increase in output) at the end of the period an indication of a higher utilization potential? Does that mean that with more effective management a company can grow by adding fewer employees proportional to the revenue growth? This sounds very optimistic and possibly only doable to a certain extent.
I’d love to hear your personal opinions and actual experience and observations in your own companies.
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