Our research with supply chain professionals at consumer goods companies found that 55% consider On Time and In Full (OTIF) orders, or so called “perfect orders,” one of their top three KPIs. That’s the highest percentage out of all metrics we asked about, including On Shelf Availability (37%) and forecast accuracy (34%). Even the highest levels of the organization recognize its importance: 60% of C-level executives consider OTIF a top three KPI.
Suppliers clearly have their eye on customer service and in fact, understand its importance beyond the cost of retailer penalties. The same survey showed only 33% considered reducing OTIF fines a high priority, compared to 54% for improving fill rates. And 64% put strengthening customer relationships near the top of their priority list.
So while it hurts each time you’re charged a fine, simply playing whack-a-mole to try to prevent fines on specific orders or dispute them after the fact doesn’t really help achieve your goals. You want to show customers you’re a reliable supplier and will keep shelves stocked for consumers. We recommend taking a more systemic approach. Look across all your retailers (whether they charge fines or not) to address your OTIF “problem children” and improve service.
For example, Alloy helped one of our customers identify the five main products that caused service heartaches. This insight focused their team as they directed their supply chain to prioritize these particular items.
The first step is, as always, gathering useful data for analysis. We’ve looked previously at what Walmart shares, both at an aggregate and PO level, to assess your OTIF performance at the retailer.
Kroger is another retailer that provides good data. An Excel scorecard and line item detail of truck arrivals at Kroger DCs help you examine OTIF in more detail. Meijer’s portal provides one report with On Time performance and a separate one with In Full Data.
Just looking at this small set of customers (although likely big in terms of the portion of your business they represent), however, we see inconsistencies. Different partners provide the data in different formats, at different levels of granularity. They even compute the “On Time” and “In Full” metrics differently.
If you were in charge of analyzing OTIF, you would need to maintain three different spreadsheets, each with different data models and formulas, so you could understand each retailer the same way.
And what about all your other customers who provide even less data?
When your focus is on understanding OTIF for the purposes of improving performance, instead of simply combatting fines, you can often use more readily available data from your internal ERP data and/or 3PLs. It’s also more likely to already be in a more consistent format, so you don’t have to harmonize it first. You can just apply a consistent method to calculate these metrics.
On Time is the number of units that arrived on the agreed Must Arrive By Date (MABD), out of the total units received over a given time period, typically expressed as a percentage (Units arrived on time/Units received *100%). You can look at your shipments for the total units received. To determine if a unit was On Time or not, you have a couple options:
Then you can sum up the units that were On Time and complete your calculation.
Similarly, In Full is the number of units that the customer received out of the total units ordered over a given time period, typically expressed as a percentage (Units received/Units ordered *100%).
You can base whether a unit was received on the arrival data from the retailer or 3PL, or shipment data from your warehouse. Then using POs to see how much the customer ordered, determine your In Full percentage.
Multiplying the separate On Time and In Full metrics leads to the single OTIF metric. However, we’ve seen the industry moving away from this practice and reporting them separately. It’s much more helpful for solving issues to know whether late shipments or incomplete orders caused poor performance.
One important thing you’ll notice is we use the generic term “Units” to calculate these metrics. You want to get down to as granular a level as possible and put it in whatever terms your company uses to think about your products. Too often, OTIF is reported at a PO level or even just in aggregate. This averaging out washes away what you need for root causes analysis and an actionable response.
Say a PO is only 50% in full. Which SKUs were shorted? Was it just one product with very poor performance dragging down the whole PO? These are questions you would have a hard time answering to get to what needs fixing.
Once you have your data collected and in a usable form, the “fun” begins. You can compare performance of different products, review changes over time and slice and dice it in different ways to identify what’s causing your OTIF issues. This analysis is the most powerful when it covers all your customers, so you can spot larger trends and accurately prioritize the most pressing problems across your supply chain.
Keep in mind problems aren’t necessarily going to be tied to a product though. They could be related to factors of the shipment, such as the originating warehouse or the logistics partner. Or even aspects of the order, such as if there were last minute changes or how closely it followed the retailer’s forecast or your forecast.
Consider all the aspects that could have an impact on your ability to fill an order On Time and In Full and segment your performance by these dimensions to see if they’re a culprit.
From there, just keep asking the next question to help you identify how to address the problem. If it’s a particular product category, is it because demand suddenly spiked and orders significantly exceeded forecast, or because you have supply issues (or both)? If it’s a supply issue, is it because you can’t get enough materials or is something wrong at the plant?
By systematically and regularly going through this process to address your problem children, you can improve OTIF across your supply chain – and potentially reduce other headaches too!
Tracking OTIF fines as part of this analysis can help you decide what to prioritize. Most likely you’ll have multiple problem children, each of which can require a lot of effort to address. By associating a dollar cost to each of them, the question of where you should focus first becomes a lot easier to answer, much the way lost sales dollars helps you prioritize where to allocate inventory.
At the end of the day, fines are a strong motivating factor. For example, you might determine one option to improve OTIF is increasing safety stock of certain products at a couple of your DCs. There’s obviously a cost associated with tying up capital that way. Whether it’s justified depends on the penalties you could avoid, not to mention the impact on out-of-stocks and customer relationships.
The speed and flexibility of Alloy POS analytics enabled this consumer brand to make more timely decisions for new product success and inventory management.
ViewThe global confectioner mitigates waste, improves service levels and controls costs by connecting digital supply chain visibility with POS analytics.
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