As successful companies grow globally, they must follow two seemingly paradoxical paths. First, they need…
There’s an old saying that you should never bargain shop for brain surgeons or parachutes. I propose that the same advice holds true for selecting BI and analytics software, which today feed the lifeblood of large enterprises.
Unfortunately, one of the primary objections I often hear from prospects is “We only need a small portion of what your platform offers.” And all too often, their conclusion is: “We like what we have already. It’s good enough.”
Perhaps one reason for this reticence to consider a change results from their hard-fought battle to bring in a current vendor, and the lack of perceived benefits they obtained at their line of business level. Another may be due to shrinking budgets or an inability to demonstrate ROI from too many BI platforms of the past.
But those rationales are more often taken from a piece-meal perspective, one that looks narrowly at the one line of business or region where the system was deployed, with little regard for how the entire enterprise could benefit.
Instead, companies are better served today by a bi-modal analytics approach. In doing so, a company can enable top-down modeling to set KPIs and conduct enterprise planning and forecasting, together with bottom-up intelligence feeds from their lines of business, which provide those business analysts (aka citizen data scientists) the freedom to conduct their own “what-if” scenarios and analyses.
In a recent Gartner report on bi-modal analytics (www.gartner.com), the firm advised clients to, “Evaluate new alternatives to traditional IT-managed BI architectures that are more flexible and agile methods of preparing, integrating and governing data for analysis, thereby widening data access to a broader range of users.” Taking such a strategic, enterprise-wide view of a company’s BI environment without losing the grass-roots analytics from lines of business raises the stakes far higher than just a departmental solution or traditional ones isolated in headquarters.
Moreover, the considerable results such companies are enjoying from bi-modal approaches are light years ahead of traditional BI. In fact, they raise the bar on what “good enough” analytics really are in 2016.