Value comes in many shapes and sizes in today’s ever-evolving world of intelligence delivery solutions
Insight … ‘the act or result of apprehending the inner nature of things or of seeing intuitively.’ Thank you, Merriam-Webster. Business Intelligence. Advanced Analytics. Big Data. Operations Intelligence. The Internet-of-Things. And on and on it goes. It’s all about gaining insight.
More likely than not, we’re all doing some pretty clever stuff in the realm of intelligence delivery today. At the same time, it seems that we may be losing fundamental ‘insight’ when it comes to differentiating and understanding the unique value proposition these various intelligence-focused capabilities mean to an organization. Yes … It’s become a bit of a mash-up on the intelligence delivery front and that’s not necessarily a good thing. So please … allow me to get intuitive.
Let’s start with the underlying premise that the alphabet soup that’s evolved in the brave new world of intelligence delivery has left far too much to the imagination. My most recent read of Gartner’s 2017 Annual Analytics Report only reinforces this. Intelligence delivery demands context. And clear understanding of context is what defines value. At the end of the day, it’s value that holds up any new intelligence capability. Whether in the form of cost containment or revenue growth. In a later piece, I’ll dive into these value drivers, as they relate to the manufacturing industry.
This is an age-old problem that plagued early BI deployments from the get-go. We embarked on infrastructure projects with the promise of building a temple that would deliver on wisdom that we all longed for (i.e. the Data Warehouse). So we sold the concept and built a team, investing significant resources with the promise of one day flipping the switch and bringing wisdom to the masses. That road was littered with one failed deployment after another.
At the core of these many failed BI initiatives was a lack of context. Context in the sense of specific problems we needed to address and the associated financial opportunity. BI Ver. 2.0 started taking on a much more context-oriented strategy as the notion of the functionally-focused ‘data mart’ took hold. The financial, sales and operations focused data marts not only allowed an organization to eat the elephant one bite at a time, it created a value-driven mindset to go after the low hanging fruit in a much more timely and incremental fashion.
Fast forward to today and the new world of IoT. The nature of this beast brings an entirely new level of abstraction to defining value-driven context that can best leverage the key attributes inherent in this new intelligence delivery model. Our heads want to take us to the structured data environments that have anchored the overwhelming majority of intelligence deployments we’ve stood up over the past 15 years…
Just as BI was in the early going, IoT is a unique intelligence delivery model that will deliver significant new value to the market in the years ahead. What we learned from that earlier era was the need to focus on context-driven models that drove clear value creation. And that’s a lesson we must hang onto.
This is the business of insight. As Merriam-Webster tells us, insight is … ‘the act or result of apprehending the inner nature of things or of seeing intuitively.’ When we approach intelligence delivery with a lens that creates an intuitive view to the otherwise unforeseen nature of things, then we can say – and will say – we did our job well.
About me, Scott Lee.
I recently joined the team at eLogic to help focus our efforts on the delivery of high-value, next generation intelligence capabilities enabled by the likes of IoT, Machine Learning, and Advanced Analytics. As a key industry partner to Microsoft, eLogic has taken a leading role in helping bring context to the new world of IoT in today’s digital economy, in a way that is specific & relevant to manufacturers.
For me, Business Intelligence was the first act in what became a ground swell of enabling technologies that would unleash my early passion for this thing called Management Science. My work with the early BI platforms such as Business Objects, Cognos and Microstrategy unleased the world of transactional data, delivering insight from what had previously been looked at as little more than data stores for a company’s many business transactions.
That early experience positioned me to take a role in advancing the technology, introducing the power of content, search and text analytics to the highly structured world of BI. It not only enriched traditional BI environments, it also introduced the notion of machine learning. That is, providing the power to identify and retain patterns of associated data and content that typically went unnoticed in our pre-engineered, structured BI environments. For me, it was then that ‘intelligence’ matured to a much higher level. Truly that of ‘insight’.
With that, my early work with eLogic will have a large dose of mapping out the ‘what, why and how’ driving the future of intelligence delivery anchored on new models of value creation in the market. Particularly within the Microsoft Azure IoT environment. My early blogs will do my best to help you delineate and navigate the technologies that will drive this sea change. Always with a focus on the ‘why’, the use-cases defining the business models of the future and - of course - the value that will be realized from these new capabilities.
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