I came across a customer the other day who was faced with the following problem. The customer has many trucks on the road. Although the planning of these tracks is nicely optimized, a lot of time (and money) is lost in traffic jams. The customer got really frustrated that despite his road planning system, his business suffers from a severe time loss. Not only do some of the shippings arrive too late, but some of the itineraries could have been better planned if he were capable of taking those traffic jams into account...

The problem here is that the customer uses all information he has at his disposal internally, but due to external factors –in this case traffic jams- internal data alone doesn’t allow him to optimize his planning.

The customer was already thinking about how to take these delays into account. Many of those are predictable. E.g. he knows that a truck who needs to drive north to south in Belgium will get stuck on the Brussels ring around 7am on Monday. However, if the truck hits the ring before 6:30am, the time loss will be minimal. The customer had a vision of a solution to this problem. The biggest challenge though was the process. How to integrate this external information in such a way that it can be combined with his own internal data to work out a planning for his trucks? And how to automate this process so that this external data (which is readily available on internet – Google maps in this case) is automatically used to enrich his own information and make it a smooth process.

And that’s exactly where data preparation and data blending comes in. I had been using Alteryx to solve a similar problem I was faced with: driving from Luxemburg to Brussels at the best possible time on a Monday afternoon.

Alteryx is a data blending technology that enables you to pull data from internet, prepare it and blend it with your own data. This enrichment process lets you take better decisions based on data that comes from your internal sources but is enriched with external data. In this planning case, it’s not related to big bold decisions but rather to micro decisions (because that’s basically what road planning is about).

On top of that –and that makes Alteryx really powerful- you can visually build workflows that are reusable, so that the whole data preparation and blending process is done in an automated way.

In this example, the ROI of Alteryx can be expressed in the (partial) elimination of useless time spent in traffic jams, but also prevents penalties because of delayed deliveries.

Think about the richness of external information available on internet or from your customers or partners. I’m sure that blending this information with your own data will help you make better decisions … or save time and money.

If you’re interested to know how I managed to do this, please read my technical blogpost here. (because of confidentiality, I’m using another case but the process is similar).

If you want to know more about Alteryx and what it can mean to your business, visit our Alteryx webpages.

“Without data, you’re just another person with an opinion”
(William Edwards Deming)