I’ve been quite the world traveler recently, and I’ve talked to executives from companies around the globe about their analytics needs and what their take on the future of analytics will look like. Among all these conversations, there were several recurring themes that sound like emerging analytics trends. So in the interest of keeping my pundit reputation intact, I thought I’d address these trends in my first column of the year.
The first theme that surfaced with just about everyone I talked with – from other pundits to CEOs – was the increasing sophistication of analytics software and the need for a simplified approach to presenting the results of complex analysis. Analytics tool vendors have realized over the past couple of years that to be effective and reach the widest audience, analytics software should present the results of sophisticated analysis on large and complex data sets in an easy to read, actionable format. As a result, most tools today have advanced visualization capabilities – so much so that sophisticated visual presentation has become an absolute requirement for analytics tools.
The next trend that I see is the transition of analytics out of the office and onto the mobile devices of executives. For some years now, sales reps and field technicians have been able to perform simplified analytics on handheld units. However, true analytics functionality has been lacking – especially the further up the management chain you are. Now, with the advent of improved mobile operating systems and widespread adoption of standardized mobile platforms, mobility has moved from the wish list to the must-have list. It helps executives achieve true collaboration – no matter the location or the time – with analytics delivered via mobile technology. With mobile analytics, whether you’re in Budapest, Bangkok or Baltimore, you can have the information you need to make decisions when you need to make them.
The third trend that I see is that companies are starting to realize that analytics gives them to gain a competitive edge. In their book, "Competing on Analytics,” Tom Davenport and Jeanne Harris define an analytical competitor as an "organization that uses analytics extensively and systematically to out-think and out-execute the competition.” These analytical competitors use analytics as a strategic weapon to share information enterprise-wide, grow revenues and streamline operations in hopes of winning in this ultracompetitive, highly economically unstable business environment.
A trend that is particularly worrisome is the problems that many companies are having dealing with “big data,” which is the term being bandied about to describe the combination of growing data volume and complexity. To be able to leverage analytics software effectively, it‘s essential to have a handle on how much and what types of data you have to analyze. I’m not advocating having a completely perfect data set to work with (there’s no such animal), but I do think it‘s important to have the tools and policies in place to help achieve data quality in critical areas. It’s also essential to be able to work with both structured and unstructured content. Finally, it’s also a necessity to have newer parallel processing technologies in place to handle the sheer volumes of data required to run the complex analytical algorithms that can help you spot emerging trends and potential problems.
Lastly, and perhaps this will be the biggest sea change of all the trends that I’ve seen emerging, is that agile development techniques, new data quality tools and methodologies, and technical innovations like in-memory analytics are taking analytics (and business intelligence in general) out of the realm of the data warehouse. I made a comment to someone the other day that mobility, coupled with agile development techniques, was going to be the death knell of the enterprise data warehouse.
Now, I admit that comment was hyperbole, but in essence, I meant that with the demands executives are placing on IT in the form of more complex information in near real time – with a short development lifecycle – the enterprise data warehouse will likely be relegated to a supporting role and an aggregative function rather than the mainstay of reporting and analysis. Instead, I think that companies will store data in their warehouses for distribution to mobile analytics consumers and for use in temporary one-off applications that may or may not survive long-term.
I’m not saying that I have a crystal ball; no one does. Nor am I saying that all these trends will play out just as I’ve suggested, but the signs are there that analytics is leveling the playing field in IT. It doesn’t matter anymore that companies do or don’t have millions of dollars to spend on analytics. The tools and development techniques available today help just about any company with competent IT people to compete with analytics. More competition is a good thing – for everyone.
This publication contains general information only and is based on the experiences and research of Deloitte practitioners. Deloitte is not, by means of this publication, rendering business, financial, investment, or other professional advice or services. This publication is not a substitute for such professional advice or services, nor should it be used as a basis for any decision or action that may affect your business. Before making any decision or taking any action that may affect your business, you should consult a qualified professional advisor. Deloitte, its affiliates, and related entities shall not be responsible for any loss sustained by any person who relies on this publication. Copyright 2012 Deloitte Development LLC, All rights reserved.
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