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As we progressively march towards a Big Data-powered world, there seems to be a pervasive friction (even an all out war in some organizations!) between proponents of onsite Business Intelligence (“BI”) capabilities and those advocating for a full migration to the cloud.
Breaking from the past is always so romantic, refreshing… easy! Even more so when IT departments have built a reputation for their poor management of strategic business solutions. So here comes The Cloud: a beautiful, almost saintly entity floating above all mortals and promising none of the pains associated with the heavy hardware that alienates human beings in the dungeons of our corporate buildings.
Don’t get me wrong. I make a living out of cloud-based software. And I am a serious proponent of business-driven technology and CMTOs, but I also worry about the consequences of excessive hype, experienced too many times before. In fact, I should now quote SAP’s Timo Elliot (check out his post on Business Analytics vs. Business Intelligence):
When people introduce a new term, they inevitably (and deliberately, cynically?) dismiss the old one as “just technology driven” and “backward looking”, while the new term is “business oriented” and “actionable”.
So, where are the caveats?
For a start, there are many degrees of cloud. The kind of private cloud required by many highly-sensitive business processes is not at all detached from internal IT capabilities, but on the contrary extremely dependent on them (you may be paying someone else to fan the ovens, but they are still solely yours).
Secondly, not all data sources will eventually reside in the cloud, thus supporting the case for a simpler cloud-to-cloud transition. There is still a long way to go before certain internal processes are handled by third parties.
Finally, data integration has extremely complex legal implications (primarily related to privacy) that multiply when third parties come into play (think “data processors” vs. “data controllers” in the UK legal jargon). These have been largely obviated in recent times, but will not be in the years ahead.
Do I mean that we should all stick to the same old BI systems we have suffered for years? By no means. But I believe we should give each side credit for what it does best under the specific circumstances of each organization.
There will undoubtedly be huge differences here between pharma companies, utilities, financial institutions and e-commerce startups.
Now, What is the one thing that the cloud can invariably handle better? Information delivery.
Information/data delivery is about “light data”. It is about aggregate data that cannot be drilled-down to the individual level (privacy concerns dissipating as a result). It is about pre-processed data that simply needs to be served to stakeholders, ready for consumption and true “decision-making support”, wherever they are.
In summary, this what the winning formula will often boil down to, despite all the hype:
Here is (in simplified format) the extreme scenario of 100% onsite storage/integration and analysis (the case at some large banks), supported by cloud-based information/data delivery nevertheless.
– Cloud-based information/data delivery: profiting from the efficiencies of cloud-to-cloud transfer (via APIs) for certain data types that may be ready for direct consumption or high-level correlation (social media, file management, web analytics, digital marketing, etc.) while loading just enough back-end and pre-processed aggregate data for the purposes of communication.
– A varying degree of the on premise and cloud data integration and analysis capabilities that could result in:
Of course, there is a lot to it and I am barely scratching the surface. But I strongly believe we should put the focus on that little part of Business Intelligence/Analytics that does make the most out of the cloud as of today.
Your thoughts?
Founder & Chairman at Sweetspot. Author, speaker on analytics, marketing technology, privacy compliance. JD, LLM (Internet law). Once a dually-admitted lawyer. Father of three. I love surfing and cooking.
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