Decision Chain Management

Decision Chain Management

If you have a task or question that requires insights or different angles we are open to experience your challenges. We would love to learn more...

Our professional playground is most simply described as Data Driven Decision Support for Traffic.
When the “buzz” came along with Machine learning, and AI and then deep learning what we do became a big black box, where some "thing" just happens to work. Inside this black box is exactly where we work, but we usually call it a decision chain and what we do “decision chain design or management”

Let us start with data, zeros and ones, and lots of them – in them selves absolutely and genuinely worthless unless you are the company making money transferring and storing them. For the rest of us the value of data is realized when we decide. We can show all kinds of colors, graphs, KPIs - but it is only at the decision point that the value of data is harvested.

That gap – from data to decision – is bridged with what we call a decision chain.
Everything that happens in-between – like collection, transformation, augmentation, refinement, etc. are all links in the decision chain.

We work with any kind and perspective of decision chains:
- The strategic perspective, rare, long term/very invasive/very expensive decisions, like deciding to build a highway or mayor infrastructural changes.
- The tactical perspective, medium term/slightly invasive/low cost, like changing intersection markings or reprogramming an intersection, and
- The operational perspective, immediately applicable/repetitive/”no” cost, like green time extension/bus prioritization.

Also pre- and post decision analysis and evaluation are within our working scope.

Programming/Implementation is an intrinsic part of almost everything we do. Sometimes the need for programming is so obvious that we don’t even mention it. For that reason potential customers may have questions as to what programming languages we can work with. And even though we still know of programming languages that we have had no experience with (Haskell and Lua, to name a few) we have experience with almost any relevant programming language to solve any task today.