Over the past few weeks we’ve published a series of articles on this blog, aiming to broaden the definition of self-service business intelligence (BI).
It’s a topic that’s on everyone’s lips nowadays but somewhere in the hype cycle it has become almost synonymous with Data Discovery, and the notion that regular business users should be given access to raw, unstructured data to gather their own business insight.
We’re fond of quoting Mico Yuk’s infamous statement on BI adoption on this blog: “User adoption is the only metric that matters in BI.”
This is something we are passionate about at Antivia, because we believe everyone in an organization should have the information they need to help them do their job effectively, regardless of their job title or where they are based.
However, despite growing investment in BI, it appears adoption rates have been stuck stubbornly around the 20% mark for the past several years.
Lean and agile business intelligence is another hot trend in 2015. According to the experts, the key to BI success is moving away from the waterfall model and towards a circular one, where you plan, deliver, evaluate and iterate in short cycles.
But how do you go about becoming lean? How do you get to the point where you’re doing lean BI? It’s all well and good knowing that you need to be lean, but actually doing it is different.
Have you ever been in a situation where someone’s tried to give you something you didn’t really ask for and tried to pass it off as the same thing?
You know, when you order a Coke at a restaurant and the waiter says: “We’ve only got Pepsi – that’s OK, right?” And you’re left having to say that it’s fine, but end up thinking it’s not what you asked for?
The same thing is happening if you’re being offered SAP Lumira as a replacement for SAP Dashboards (aka Xcelsius).
How about taking raw data from several source systems, transforming this into a data warehouse and delivering a suite of interactive dashboards on top that can be used by frontline workers across your organization – taking you from data to business insight in a couple of weeks? Then, how about adding more data and more data sources to support changing business needs – delivered as a series of further short phases?
He underlines that it is “critical to understand how location affects business”, and that analyzing the location element of data properly can “provide insights that support and improve decision-making in everything from marketing to supply chain logistics and operations”. However, Moreno points out that most traditional business intelligence platforms lack this functionality.
As someone who has previously written (here and here) about how technology labels often don’t help us, you might think it a little odd to find me writing a post comparing one label (BI Apps) with another (self-service BI), but bear with me.
I came across an article written by a product marketing chap, which draws an interesting analogy between doctors needing patient information and corporate users of BI. The article is not recent, but we still see a trend, especially from vendors, claiming that self-service BI is everything business users need.
The author of the article asks us to imagine a scenario where doctors are not allowed to access data directly, but instead have to go and ask non-medical, data-specialists for the information, sometimes waiting hours or days for the answers. Clearly, this is supposed to be a parody on the way BI works in some organizations and equally clearly this would be a ludicrous way to run a hospital.
I like to cycle. When I’m out riding my bike I have a little computer attached to the handlebars that, amongst other things, tells me how fast I’m going with a little arrow alongside indicating whether I am travelling faster or slower than my average speed for the ride.
Underpinning this arrow is a well-known formula: speed = distance / time. If I was a scientist or a mathematician I could go back to the first principles to demonstrate the proof of this formula.
However, when I’m riding my bike I don’t need to know, nor do I care about, any of this.