Four ways analytics is going to change over the next decade

Simon Electronic Game

Anyone else remember these?

We've come a long way. Things change, and they change quickly; the only eternal truth is that nothing's constant. It's glib, but it's true. And, those who don't (or can't) adjust get relegated to the history books.

There's a storm brewing and, by my bet, the nearer term future for analytics is going to look vastly different to the way things are today. Bob Flores, ex-CTO of the CIA said earlier this week at a joint IAPA / Greenplum event that in his time working in intelligence, he's seen the problem domain shift significantly. One thing that really stuck with me was that the NSA was dealing with Big Data (proportionally) as far back as the early 80's. In a time when the 3½-inch single sided disk had just been launched with a storage capacity of 280 kilobytes, they were already dealing with a production system capable of storing over 100 gigabytes of data.

Staying ahead of the curve isn't easy. But, it's important. And, here's some of the issues we, as a discipline, are going to need to deal with over the next decade:

  1. Near-enough isn't good enough. It's real-time or nothing. We're already seeing leading-edge organisations move past 'right-time' and into 'real-time'. Much of this is being driven by shorter windows to act due to greater activity in social media, better front-of-house customer relationship systems, the rising prominence of high frequency trading, and the importance of halting transactional fraud in-stream, not after the fact. Most of the banks in Australia are rebuilding their core banking capabilities from the ground up in preparation for the next decade. The same is true for most of the telcos. As their newly developed capabilities come online, there's going to be a groundswell in interest around how real-time analytics can capitalise on new markets, reduce time to market, and shift organisations from being responsive to interactive. Don't underestimate the significance of this shift, what becomes possible, or the complexity of execution for a larger organisation operating in a complex ecosystem.
  2. There aren't enough people to do everything everyone wants to. And, there won't be. There's a gap between the skills available within the market and the underlying demand for people. And, it grows every year - at an industry level, we're just not producing enough graduates to fill the demand for analytically-intelligent people. And, those who are trained are more often than not being given only a subset of skills in demand by the private and public sector. While there's a good focus on core statistics and mathematics, recent graduates rarely have a good understanding of the importance of the human, political, and operational sides of business analytics. This is going to inflate wages for those who know how to unlock the value of analytics, in turn creating significant wage pressure for organisations after those with the skills. Good news if you're the person being paid, but it's going to be an increasing headache for mid-sized organisations trying to compete with the larger enterprises. For organisations that really succeed in business analytics, innovation and creative solutions are going to be the norm, not the exception.
  3. Not everyone's equal. The market will find a way to tell the difference, but only after a great deal of confusion and frustration. Rising wages will encourage a flood of people with dubious skills looking for work. Unfortunately, it's extremely difficult at the moment to distinguish between those who talk a good talk and those who actually know what they're doing. The importance of identifying those with skills from those without will eventually lead to the general adoption of various industry certifications, domain certifications, or other market signals. Unfortunately, this will probably only be after significant frustration and wasted productivity. If you're an existing practitioner? Keep your eyes open and be ready to validate your skills, whether it's through industry associations, certifications, or peer-validated social networking.
  4. Classic analytics consulting models will start to break down. In their place, new offerings will grow. The typical response to a lack of resources is to start hiring consultants. And, in analytics, this normally means giving away the keys to the kingdom by outsourcing all the real value and IP to a third party. However, as understanding grows of the importance of business analytics as a competitive differentiator in its own right, the willingness of organisations to relinquish this value will drop. There's already a general resistance to using consultants for value-creating analytics in many organisations - this isn't because they don't want to use consultants, it's because they've recognised that they need to own their value-creating activities. Because of this, offerings such as 'results as a service' with the option to internalise the processes and technology at some stage in the future will become more and more prominent.

What do you think?


  1. Toronto criminal lawyer
    Posted July 5, 2011 at 2:30 am | Permalink

    changing is just a trend in the next decade. and it must be a good change. everybody nowadays maybe are not believable what will happen after ten years later,but we'll be familiar with it at that time. the time change the world as well as us.

  2. Michele Chambers
    Posted July 5, 2011 at 7:25 pm | Permalink

    Hi Evan -
    Thank you for the thought provoking topic! For full disclosure, this is Michele Chambers, GM & VP of Analytic Solutions at Netezza, an IBM company.
    Here are some of the ways that I think our world will change in the next decade:
    1. Infusing of Analytics. Analytics will be integrated into strategic, operational, execution information systems rather than being an afterthought as they are often today. By infusing analytics into applications we leverage the limited analytic talent/resources.
    2. Analytic performance matters. As you point out, analytic performance is critical and there will be more and more real-time analytics processing. Additionally, there are many situations where the performance is tied to on-demand analytics processing. This is key when the best laid plans go astray (as they inevitably do) and the front line needs to make the next best decision as fast as possible considering as much data, constraints and variables as possible.
    2. Trade-off decisions. Enabling the front line with the ability to make optimized trade-off decisions is going to be critical as the complexity of the world continues to increase and we move towards micro-decisions.
    Watch our blog at: for more thoughts around these topics in the next couple of months.
    Michel Chambers
    GM & VP Analytics Solutions
    Netezza, an IBM company

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