This is the first blog post in a series of three articles by Mikkel Kvist

Mikkel Kvist is MT Højgaard’s Head of the Group Business Intelligence Competency Centre, where he bridges the gap between Business and IT. 
In this first blog he reflects about the reasons for going from hand-coding to automation, in the 2nd blog about the objections he met, and the 3rd blog about combining the old way of doing things with the new way.

As a major construction firm, MT Højgaard inhabits a difficult, complicated business world. From our headquarters in Søborg, Denmark, the company is involved with building bridges, mining in frozen wastelands and installing offshore wind turbines in stormy seas. Major infrastructure projects such as these are hard enough without backup systems adding further complications. That’s one of the reasons why we now have a Business Intelligence Competency Centre, which promotes rapid, data-driven decision-making processes across the entire organisation, based on one set of high-quality data.

Everyone wants BI to be effortless, fast and accurate. But that isn't always the case. Do any of these starting conditions sound familiar?

1. Your existing data warehouse is not used on a day-to-day basis

The goal of business intelligence (BI) is to democratise information by giving staff the data they need, when they need it. Before the BICC got started, our IT department had already built a data warehouse and a financial cube, but neither were being used much on a day-to-day basis. Having made this investment without harvesting any obvious benefits, BICC was tasked with bringing this data into widespread usage by kick-starting a cultural shift backed up by appropriate user-friendly systems.

2. You have a hard time finding IT and BI specialists

One of the main reasons why we started considering automation was that we appreciated a tool that could empower people who had no technical background. We wanted to know whether we could sidestep the limited number of specialists available to us by having a lot of tasks done by different departments that were historically done only by the IT department. Share the load, as it were.

3. Business users ask for self-service BI

Our goal is to be able to bring in data from various sources, prepare it to a certain level and then allow different departments to build their own models. They'll never be totally on their own, but the more they can do themselves, the more we can focus on the process of giving them analysis in ever more sophisticated ways. This is what I would call “assisted self-service.”

4. But business users are not capable of saying what they need

And that’s my crucial point. Our business isn’t used to rapid, almost real-time data analysis. When it is, that will be the cultural shift I was talking about. It can be difficult for any department to tell us what they want because they don’t yet know what we’re capable of. Because of that, building reports is proving to be an iterative process, where we’ll prepare and present a report and then be asked, “Okay, can we now tweak it in a different direction?”

With the data warehouse automation provided by Discovery Hub, the answer is usually yes. We can now build rapid prototypes by starting fast, failing fast, and then quickly producing improved results as other parts of our business discover what is possible from the platform. We’re realising that the more specialized knowledge we have on any specific area of the BI value chain, the more we can work on the entire value chain. Knowledge of tools such as integration, analysis and reporting services actually turn Discovery Hub into a more specialized tool – you just need some extra knowledge of these domains to benefit from it.

That’s where we are right now. How we got here, how we moved away from hand coding and coped with the change over to a largely automated system is what I’ll be writing about next time.

Mikkel Kvist is MT Højgaard’s Head of the Group Business Intelligence Competency Centre. The MT Højgaard Group a major construction and civil engineering player in the Nordic countries, employing 4,200 staff and generating an annual revenue of DKK 6.8bn.