The way it is put in a recent Business Week article is this (they describe Business Intelligence software rather than data mining software, but the principles are certainly similar):
Interest in business intelligence software is on the rise, analysts say, as economic woes force companies to pursue profit by delving deeper into the information already at their fingertips. "There's a tremendous pressure on cost containment, on developing accurate forecasts of sales and expenses and trying to align the expense stream with projected revenue stream," says John Van Decker, research vice-president at research firm Gartner (IT).
And where software is purchased, there is usually many times more the cost of the software in training and consulting to help understand better how to use the software,
Add in other essential services, and a company can expect to spend more on BI than for other types of software, Evelson says. "For every dollar you spend on business intelligence software, you better expect to spend five to seven times as much on services," such as ensuring it jells with the rest of the company's software, he says.
But even with software, unless there is clear thinking about the problems that need to be solved, and which ones can be solved realistically (or impacted) with analytics, the software will just sit, doing nothing useful. This is surely a factor in the divide between potential capabilities in analytics (i.e., software on the shelf) and benefits attained by analytics:
Still, about two-thirds of large U.S. companies believe they need to improve their analytical capabilities and only half believe they are spending enough on business analytics, according to an Accenture (ACN) survey of 250 executives that was released in December. In it, about 57% of companies said they don't have a beneficial, consistently updated, companywide analytical capability, and 72% are working to increase their company's use of business analytics. Today, only 60% of major decisions are based on analytics, according to the survey, while 40% are based on intuition.
The better consultants work themselves out of jobs, rather than perpetuating the problems. (check out despair.com for tons of hilarious posters).
Just more information that these are good times for data mining.
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5 comments:
The recession is also driving small businesses to become smarter about their data. Costs are decreasing for both talent and technology during the recession, increasing access to more advanced analytics.
As you point out, it is necessary to have "clear thinking about the problems that need to be solved" before wasting time and effort. Too often managers are focused on unactionable data and metrics. By spending time up-front to brainstorm success metrics you can set realistic goals and increase buy-in.
This from an interview with Karl Rexer from the LinkedIn Analaytics group:
Ajay -Could you please share some sneak previews of the survey results? What impact is the recession likely to have on IT spending?
Karl- We’re just starting to analyze the 2009 survey data. But, yes, here’s a peek at some of the findings that relate to the impact of the recession:
* Many data miners report that funding for data mining projects can sometimes be a problem.
* However, when asked what will happen in 2009 if the economic downturn continues, many data miners still anticipate that their company/organization will conduct more data mining projects in 2009 than in previous years (41% anticipate more projects in 2009; 27% anticipate fewer projects).
* The vast majority of companies conduct their data mining internally, and very few are sending data mining off-shore.
I don’t have a crystal ball that tells me about the trends in overall corporate spending on IT, Business Intelligence, or Data Mining. It’s my personal experience that many budgets are tight this year, but that key projects are still getting funded. And it is my strong opinion that in the coming years many companies will increase their focus on analytics, and I think that increasingly analytics will be a source of competitive advantage for these companies.
It is surprising to see how companies have still not utilized the full capabilities of analytics. In a reent panel discussion that i heard, two big US companies (healthcare) still rate themselves between 5-6 on a scale of 10 in analytics.
Many small business lack in their understanding of analytics and some time misunderstand Reporting or probably OLAP based tools as analytics.
Also, it is only now that the companies are understanding the importance of analytics and how the money spent now can bring greater returns later. There has always been a mismatch between the focus of the CFO and the CIO/CTO and many analytic projects have not taken off because of short term pressures in achieving the targets and because of analytics not being part of the CFO's budget.
I've also had recent interactions with decision-makers (and recounting of interactions with decision-makers, like CFOs, CMOs, CTOs, etc.) and it's the same story. CFOs seem more likely get the ROI benefit of data mining, but it has to be a longer view because typically there is an up-front hit for software and training or a consultant in order to achieve the return (the "R"). Moreover, the up-front hits are cash near-term, whereas the benefits are often softer and trickle in.
I frankly don't see a way around it, though it can be advantageous to get those quick wins first on the easy problems (low-hanging fruit, if you will) to (1) generate the buzz with a win and (2) achieve some "R" before taking the bigger step. This is exactly what's happening now with two separate engagements (one in the web analytics world, one in fraud detection), and I think it will be a winner. But in both cases, there is definitely buy-in, so I have it easy!
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