/ Can an Agile, Efficient Data Project Exist?

Agility is a term I hear often—agile processes, agile technology—but what about agile business intelligence?

Recently, at the CIO Edge event, I spoke with a number of leading Australian CIOs and they all shared one thing in common: the need for agility, and more importantly, the value of quickly getting the right information, to the right person, so they can make informed decisions.

It’s not news that big data—and business intelligence—projects are failing. This ultimately stems from one key issue with the approach: Initiatives that start with the data, to create metrics or “find answers,” are significantly less likely to deliver business benefits than initiatives that start from the business questions and work down to the metrics and data.

I heard from a number of CIOs that their first round of BI had not delivered what they wanted.

What I have found in my work as a business consultant at Domo is that organisations that approach their data and analytics projects from the business problem down are able to deliver results in as little as six weeks, with deliverables every four to six weeks after that.

Here are the three things that successful companies do differently …

Fast time to value

Right up front, Domo conducts a Business Value Assessment, which identifies and prioritises the high-value use cases.

Picking this low hanging fruit enables us to deliver business value in as little as six weeks and establishes a positive cycle with key stakeholders.

Once the first initiative is delivers business value quickly we build start to build trust and get permission to invest more, creating a virtuous cycle.

Save on construction

The second part of the delay is often caused by building the data platform itself. Often, IT organisations buy components and integrated them.

Merging a number of point solutions means pulling together pieces that may not naturally fit, chewing up time and requiring significant technical support while reducing your ability to be agile.

Pulling all of these together is a bit like buying a Mercedes then sticking a Yugo grill on the front.

Domo already has an end-to-end platform, with everything from the data lakes to visualisation tools, available with the turn of a key to remove the lengthy construction times and streamline the data supply chain.

Our platform is extremely flexible and can also work with what customers already have in place to bring everything together, simply.

Questions are key

Asking the right questions is the most important part of the approach.

Instead of beginning with data and working backwards, we begin with the business questions that leaders and front line staff need to make informed decisions.

By identifying what needs to be answered, you can quickly tell what is a vanity metric and what’s valuable. You can also understand the value of the decision or action it drives.

From these questions you can easily define the metrics and thus the data source needed to answer these business questions.

This avoids the trap of spending too much time and money on collecting and cleaning data that is never used or is of a low value.

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