My Audi 100 was equipped with one of the first five-cylinder engines that the German car automaker produced. Although compact as a standard inline-four and smooth as a straight six-engine, it remained one of the rarest engine configurations since its introduction in 1976. However, their sound was absolutely incredible, and the engines later became very popular in motorsport, particularly in the rally championship, but also in drag racing.
A quarter mile is the standard distance in drag racing. Acceleration times differ between identical vehicles due to varying conditions like weather, track surface, etc. Setting a new world record requires strict adherence to certain regulations before they are recognized by the official bodies.
Some logistics software vendors claim that their algorithms constantly set new world records. Although this is true, some of these top marks were often achieved in classes and on distances that are non-standard creating little to no competition at all. While the fastest standing time on the 2/5 mile, in a turbocharged station wagon may deserve credit, it lacks the impressiveness of a true competition. Instead of virtual test drives, “getting in” and hitting the road is a better way to see and measure the performance of a software tool and its algorithms.
Ladies and Gentlemen, Start Your Engines!
Comparing all software vendors side-by-side is the next step in the buying decision process. It is the best chance to see how they measure up to expectations. What set-up and test track is most suited to produce reliable results and to draw the right conclusions?
Real-world data of a recent transport plan forms the basis. Three days are often sufficient, but they should be a good mix of all operational scenarios: a busy day, a typical day, and a quiet day. All vendors should be supplied with the same data set. Data should include: orders, available trucks, and depots/plants. In addition, all business rules and constraints need to be communicated clearly. Business rules could include customer/contract profitability, preferred haulier list, targets for product volumes or specific regions, transport cost, etc. Constraints include equipment compatibility of truck/loading point, opening hours of loading points, customer site constraints, etc.
An Origin-Destination (OD) matrix is a key component of any transport planning tool. It is used to calculate trip times and route distances. It is important that all vendors work on the same OD matrix, irrespective of the map they are using. This ensures that results are comparable, apple to apple.
Proper test runs need time. It is usually a process of repeating rounds. Call backs from the vendors are a good sign of commitment and attention to details. Once results come in, these should be compared with those KPIs on which the original data was based. Each KPI should be checked individually and for plausibility. Results may be distorted by “hidden data”. This is information that’s only known to the dispatcher (e.g., a truck wasn’t able to drive a specific route on a particular day). Tests should be repeated in these cases.
The Checkered Flag
A side-by-side comparison of all optimized KPIs should give a clear indication of who crossed the finish line first. Really? One might be tempted to follow this logic, but a sheer look at the KPIs is no guarantee for success. Financial rewards are the ultimate goal of transport optimization (see figure in part II of this article). So converting each KPI into monetary equivalents will reveal the true champion.
My Audi 100 saw its final flag two months after we returned from France. It didn’t pass the German roadworthy test (TÜV) which was overdue. So our final trip was to a nearby scrap yard. I still shed a tear once in a while when I think of that car. If you happen to know of a 1978 Audi 100 that’s for sale, please let me know.
Where and how did your first car end?