Is the future of analytics within your enterprise architecture a rapidly changing agile innovation platform (Lab), separated from operations and broad enterprise audience usage, alongside a consistently slowly changing enterprise analytics platform (factory) that supports operations and a broad enterprise audience? That is the question this blog digs into?
This is an important IT topic at the moment as working out how innovate and modernize at the same time is one of the biggest challenges organizations are facing right now. In the past this has been like changing to new wings while flying the plane which has always been slow and risky.
So you’ve been monitoring or are already on the journey with Hadoop — and you’re wondering: Where are we on the adoption curve compared to the market in general?
Based on my interactions with numerous companies, I want to share what I think that curve looks like so that you can orientate your organization and decide if you’re leading the way or lagging behind. Neither is inherently bad, but you do need to be conscious of where you are and why.
I answered these two questions in previous posts, and now I will answer a third pressing question: how can you build the business case once you’ve decide to develop an innovation lab?
Recently I have been out speaking with a number of organizations about the idea of the innovation lab concept , which I discussed in a previous blog post, as the way to unleash the power of big data and make even the largest of companies as agile as a start-up. During my discussions there are a couple of things that I am observing, that I wanted to share with you, since it seems there are different types of innovation labs in organizations:
Many companies have something I am going to label an IT innovation lab where they are experimenting with “big data” technologies. These IT innovation labs are NOT the same as the “data related” innovation lab that companies need to put in place to remain agile in this new digital world. The focus of the IT innovation lab is to test the technology and its integration whereas the focus of the “data related” innovation lab is to test hypothesis around mashups of data and different analytical approaches In the digital world, information gleaned from data is your best competitive weapon, and speed is a critical component to your success. It is my opinion these should be separate and distinct in a companies strategy as each has a role to play. This post will focus on the tale of two labs and how they differ.
Tight budgets, and the significantly different focus of the “data focused” innovation lab, are causing organizations to ask for support to obtain funding given it is generally a new concept to not have a concrete business problem solved as part of asking for an investment. A second post in this series will focus on how I suggest organizations can build the business case for the data focused innovation lab which I believe is vital to the future success of all organizations no matter how large or small they are.
Weighed down by what has gone before, and what is needed to keep the lights on, the CIOs at many organizations I have worked with have turned to Hadoop with the hope of utilizing it as a major component of an IT infrastructure and as part of their modernization and migration program for analytics and BI.
In my previous posts, I explored the world of traditional IT as it relates to Hadoop for those CIOs. We have looked at how Hadoop can be deployed without throwing away your warehouse and put forward some approaches people are taking around the data lake concept. All of these are generally focused on finding economically more viable approaches to what we expect to come in the future. If you like, these organizations are focused on improving what they do today while driving down costs.
In parallel to this, two questions have come up time and time again as I have worked with established organizations, of all sizes, over the past 6-12 months. Those questions are:
“How can we, with all their legacy technology constraints, hard to change processes and need to focus on cost control, possibly enable all our business units to compete with nimble competitors that are starting to cast a shadow over many parts of our business?”
“How can we challenge the age old perceptions and approaches of IT, in order to support the business in getting answers to their questions?”
