Why, oh, why is it that every time I hear about a BI project from an IT person, or from a business stakeholder describing how IT delivered it, with few exceptions these are the stories plagued with multiple challenges? And why is it that when I hear a BI story about an application that was installed, built and used by a business user, with little or no support from IT, it’s almost always a success story?

I think we all know the answer to that question. It’s all about IT/business misalignment. A business user wants flexibility, while an IT person is charged with keeping order and controlling data, applications, scope and projects.  A business user wants to react to ever changing requirements, but an IT person needs to have a formal planning process. A businessperson wants to have a tool best suited for the business requirements, and an IT person wants to leverage enterprise standard platforms.

Who’s right and who’s wrong? Both. The only real answer is somewhere in the middle. There’s also a new emerging alternative. Especially when applied to specific domains, like customer analytics. As I wrote repeatedly in multiple research documents, front office processes are especially poorly suited for traditional analytics. From office processes like sales and marketing need to be infinitely more agile and reactive, as their back office cousins from finance and HR for obvious reasons.

But there’s a dilemma. Large enterprise BI platforms are function rich, powerful, scalable and robust. But they are not agile. Excel and Microsoft Access, the most ubiquitous BI tools, while ultimately agile, are not scalable and do not have rich BI functionality. They also have minimal data integration and data scrubbing capabilities and no capability to tie multiple steps in a single process. Now there’s an answer for that something in between the two. Just like with Goldilocks and The Three Bears story, there are BI tools that are “just right” for the agile enterprise BI.

We’ve already written about “agile BI out of the box” where data centric BI solutions combine end-to-end BI processes into a single BI application, which makes it more agile (easier to design, build, implement and change). There’s now an emergence of new technologies that I would classify as process centric BI, since there’s a strong emphasis on a workflow engine (which controls parts of a processes that change frequently – through process modeling, rule management and process reporting), that ties all of the BI steps such as ETL, data cleansing, SQL and building reports and dashboards. Workflow engine is key here, since you not only automate processes using modeling (very little coding, more like assembling), you can change the processes very quickly.

This allows you to do continuous process improvement, making small changes every week, or even day, and making bigger process version changes every 3 months.

BI workflow is the core capability of the two emerging vendors in this space – Quiterian and Alteryx. Their focus is on customer and marketing analytics where workflow is especially important. Every process involves getting raw data, integrating and cleasning it, running the data against certain rules to come up with segmentation and scoring, and inserting data into marketing campaigns and other downstream applications. But even though these two vendors mostly specialize in customer analytics, there’s no reason why their technology can’t be deployed in other BI use cases.

All of the customer success stories that I heard about from these two vendors come from the marketing and sales, not IT professionals. Other than infrastructure support (and in case of Alteryx that can also be bypassed since they have a cloud based offering), IT plays little to no role in the applications built using these products. Marketing and sales operations pros install the software, keep it up to date, design and build their apps. Then they run them and distribute the results to their colleagues.

Yes, of course, I know what you are going to say. What about enterprise standards and single version of the truth? That argument works well in the back office. Most of the sales and marketing pros we talked to tell us that they’ll take quick over accurate (well, they still need the data that’s mostly – just not 100 percent – accurate) most of the time. So don’t apply “singe version of the truth” to all enterprise stakeholders equally.