The Data Heads

I mentioned in yesterday’s post announcing the release of GainSeeker Suite Version 8 that I have been working on a case study about the new report writer.

You can read the case study here, and download a PDF version to share with others.

A little bit of the back story:

This project came about during a training class we held for Valeo (the subject of the case study) early in the new year. During the class, Stacey (who is quoted extensively in the case study) made the comment “You’ll never find a kid who wants to grow up to be a data jockey.”  What a great comment.

Mel (the guy from our staff doing the training) was intrigued and scratched away at it. What did he mean by data jockey? Why had he become a data jockey? Who cared about the results of his data jockey work? What difference would it make if we could eliminate the data jockey work? What would it take to eliminate the work?

At the time, Version 8 hadn’t been released, and Mel had had only minimal exposure to the power of the new Dynamic Reports module. He came back and started asking his colleagues “So this is what they really want. Could Dynamic Reports handle it?” Dale, one of our senior developers whom I sometimes call Obi-Wan Kenobi, put together a prototype and we were off to the races.

In manufacturing circles it not at all uncommon to talk about “The hidden factory.” The hidden factory is rework. Another case study about our customer Titleist includes this analogy from the rubber and plastics industry:

Another benefit of reduced scrap is that equipment is freed to do productive work. A shop with a 5 percent scrap rate and 20 molding machines has one machine dedicated to making scrap. Using real-time production data to eliminate scrap is the equivalent of buying a new machine.

Working as a Data Jockey is a hidden factory in our offices. Like a machine producing scrap, it is not value added. Eliminating the data shuffle - freeing the data jockey - pays huge benefits to your organization. The case study outlines some of them.

What about you? What is your experience as a Data Jockey? What have you done to eliminate this hidden factory in your office? Use the ShareThis button below to mark this page, leave a comment, tweet me, schedule a conversation, or call 800-958-2709.

In my last post I shared the Data Cost / Value Matrix and described companies that I’ve known that live in each of the four quadrants. While most people aspire to Quadrant A (Low Cost and High Value data), most don’t live there in reality. Many actually live in Quadrant D (High Cost and Low Value).

While these anecdotal descriptions of the four quadrants are useful, they don’t offer much guidance on what to do about your current reality.

For that reason, I developed a quick and dirty Gap Analysis that helps you quantify where you are today. Used properly, the Gap Analysis can point you to some actions that can help you become more data driven.

(I use the term Gap Analysis because it helps you evaluate the Gap in your current performance and your performance potential. Sometimes I like to say that your performance potential is how things would work if God ran the process.)

Anyhow - here is the Gap Analysis Tool. Just answer the four questions below, then click Continue to answer four more questions. Then Click Results to see where you score.

Once you have your score, use the Back button to review your answers to each question and plot your strategy for improving your business.

Here are some questions that might help you develop a new strategy:

• Is your score better on the horizontal axis (Data Cost) or on the vertical axis (Data Value)? If you’re firmly in Quadrant C (Low Cost and Low Value) it is obvious that you need to work on increasing the value of your data. If both scores are low, look for the low hanging fruit. Often this is found in data completeness and automation. Automation will free up time from the data shuffle so that you can work at making better use of the data that you’re collecting.
• Where are your lowest scores? Often bringing one score up from Never to Seldom or Seldom to Sometimes will do a lot to improve your performance.
• Are your scores balanced across all eight categories, or are some significantly better than others? As a rule, I’d encourage you to seek a balance across all aspects, rather than strive for excellence in one aspect at the expense of the others.

These are just some of the ways you can use this data to become more data driven. Here is some information about a more complete Gap Analysis that we can help you with too.

In the meantime, does your score on this Gap Analysis reflect the reality of your business? Tell me what you think. Use the ShareThis button below to mark this page, leave a comment, tweet me, schedule a conversation, or call 800-958-2709.

I’ve tabulated the Web 2.0 Survey results, and I’m surprised by what I learned. (Isn’t that often the case when you go to the data?)

I modeled this survey on one I found in blog that serves a niche in the banking industry. I figured their survey would provide a good benchmark. It did.

The results? It looks like we’re behind the adoption curve. Compared to the banking industry where 65% of respondents read professional blogs on a daily basis, only 9% of all of our responsdents do so, and only 5% of GainSeeker users.  On a daily basis, our most popular activities are instant messaging, using an RSS Reader (which is curious, since we’re not following blogs every day), updating our Facebook profile, and using wikies.   We just don’t care about photo sharing, MySpace or FriendFeed.

If we add in our total use (daily, weekly and monthly) and what we’re curious about, videos jump to the top (95%), followed by instant messaging (65%), reading personal blogs (58%) and using LInkedIn (56%). Reading Professional blogs still garners interest from less than half the respondents (49%). Writing blogs in any form, and social bookmarking rank way at the bottom, and Twitter holds interest for less than 25%.

(Click to open full size in new window.)

Interestingly, when we segment GainSeeker Users from the rest of the respondents, they are even slower to adopt the new technology. Only 6% use some form of Web 2.0 on a daily basis (compared to 8% from the total population in our survey). More significantly, only 14% use any form of Web 2.0 compared to 31% of the general population.

Here is how GainSeeker user’s stack up their actual and potential use.

Another piece of very useful information comes from the question “How likely are you to use one of these ways to learn about GainSeeker Suite?” Not surprisingly, given the preference for watching on-line videos, we need to start making more videos. Customers also like white papers, online seminars, live users conferences and an email newsletter. They are not very interested in reading blogs or getting a print newsletter.

So my take-homes:

Given that 30% of our customers are on IM, I just set up an AIM account. You can contact me using my email address: ejmiller at hertzler dot com.  We should make publishing videos a higher priority. We’ve done a little already.  For example, here is a video about OEE (Overall Equipment Effectiveness) and Dashboards that I put together back in February. It looks like we should start shooting some more, and institute an email newsletter to promote the videos and our existing (and new white papers). We should also consider some on-line seminars. I think we could also get more mileage out of LinkedIn. It looks like there is an interest in using it, but few people seem to know what to do with it.

This captures a snapshot of our use of Web 2.0. I wonder what it will look like a year from now? What do you think? Or is there another way you’d like to look a the data? Use the ShareThis button below to mark this page, or leave a comment, tweet me, schedule a conversation, or call 800-958-2709.

If you’re on our mailing list you’ll get an email from me later today that invites you take a survey about your use of social media. If you’re not on our mailing list, consider this your invitation to take the survey now.  Here is what I wrote to my customers:

In the last few years social media has exploded on the web. Perhaps you already are Linked-In and Twittering - or maybe you’re on Facebook, and bookmarking websites with Delicious.

For the last several months I’ve been dabbling in blogs and twitter.  I can see some great potential for how we communicate with and support our customers, and how we might help our customers connect with each other. Together we can solve more problems and make the world - at least our little corners of it - a better place.

But I need a reality check. Being a data guy, I’d like to get some hard data about what you’re doing with social media today. I invite you click on this link and take a short survey. I’ll use this data to see if we can create better ways to share and discuss information among our customers. Here is the survey.

Once you’ve completed the survey, I invite you to join one or more of my networks. If you’re already on Linked-In, please review my profile and join my personal network using my email address (ejmiller at hertzler dot com). You can also sign up to follow me on twitter. Finally, you can subscribe to my blog in a reader through Feedburner.

Of course I’ll publish the results in my blog, so you can stay tuned there.

Thanks in advance for sharing your thoughts.

Interested in the survey and the results? Use the ShareThis button below to mark this page, or leave a comment, tweet me, schedule a conversation, or call 800-958-2709.

If you haven’t been following it, the discussion about the data shuffle has been continuing over at LInkedIn.

Laura Wright posted a comment yesterday:

Is there SOME value to the ‘data shuffle’? E.g., deep knowledge that can help the green or black belt discern nuances to their process analysis that otherwise wouldn’t be had…and so a better solution comes to light? Don’t get me wrong - I do believe data shuffle is wasteful…but some fruit can be gleaned from the exercise.

I think this is a great question, and I agree with her comment. But I also wanted to push the topic out a little further.

I was still trying to formulate a response when Terri Jostes weighed back in with a comment that said what I wanted to say far better than I could have:

I agree with Laura in that there is no substitute for an intimate knowledge of your data. Understanding where it came from, what it means and the process used to acquire the data is absolutely critical. But after that’s been figured out, a mechanism for streaming process data to managers and process improvement experts has to be put in place to free your belts from the ongoing task of “cleaning up” the data or linking files from multiple databases so it can be used.

In the interest of full disclosure I need to point out that Terri is a former user of the GainSeeker Suite. She comes to this after having lived with the data shuffle and found a different way of life. Actually some years ago I wrote up a case study about the experience of an unnamed Master Black Belt (who I just ‘outed’) at a financial services firm. Here is a link to read the case study, Building a Six Sigma Measurement System in Financial Services. At the end of the case study is a section on Lessons Learned, and the first lesson addressed this very point. Here is an excerpt:

Upstream manual data collection – According to the MBB who led the cycle-time-reduction initiative, the initial effort of capturing data manually first paid huge dividends as the deployment progressed. By engaging in manual data collection, the MBB was able to gain valuable insight into the nuances of the various operational definitions used by the process owners, and in the way the information system supported or did not support those definitions.

While an automated system has proved invaluable for collecting and analyzing massive amounts of transactional data, it is essential to develop an intimate, hands-on relationship with data in order to understand the system that produced it. This principle applies to any initiative or project that is focused on deriving long-term, leveraged benefit from an automated measurement system.

This lesson was reinforced later when the MBB implemented a similar measurement system in another part of the business. In this second application, she believed she knew enough about the system to go straight to automated data collection, but she discovered that there was no shortcut to forming a thorough understanding of the data by collecting it manually first. The second application took far longer to deploy, with many more false starts before realizing success.

Does this sound familiar to you? Use the ShareThis button below to mark this page, or leave a comment, tweet me, schedule a conversation, or call 800-958-2709.

Over at the LinkedIn Continuous Improvement, Six Sigma & Lean Group, I posted a discussion question that generated some great responses. Here was my original question:

Lean Six Sigma practitioner’s ad hoc data survey
Recently I was talking with a black belt who told me “I know exactly what you mean by the data shuffle. Three hours of my 13 hour day yesterday were spent doing the shuffle.”

The data shuffle is all the compiling, massaging, and manipulating data that you do to get something useful so that you can make meaningful business decisions.

My experience is that all that busy work undermines the cultural transformation that is needed in Lean Six Sigma deployments. In other words, if data were easier to get to, the corporate culture would be more apt to make data driven decisions.

I have a couple of blog posts on the topic.

For an example of the data shuffle, see http://www.hertzler.com/blog/dataheads/index.php/2008/12/doing-the-data-shuffle/

For more background on the relationship between data and cultural transformation, see http://www.hertzler.com/blog/dataheads/index.php/2009/03/hitting-my-forehead-with-the-palm-of-my-hand/

Is the data shuffle alive and well at your organization?
How much time do you spend doing the data shuffle for your projects?
Does the data shuffle undermine cultural transformation?

Here are excerpts from some of the responses:

From Shaun Wurzner:

Regrettably, [Six Sigma] arrived at a point where managers and business leaders had to demonstrate Six Sigma improvements and for fear of at best, never being promoted or at worst, being let go…. Incorporating the fear of employment with continuous improvement was in my opinion, a disastrous train wreck. As a result, managers (and I AM GENERALIZING) felt compelled to generate data to show improvement. Regrettably, the more paperwork and reports, the better chance of being viewed as a valuable results oriented contributor…

To tie back into Evan’s original question, another fundamental requirement of Six Sigma was the ability to access data to characterize process, identify sources of variation, and drive process improvement through various means… The ability to capture timely data continues to be one of the fundamental issues that challenges companies and practitioners alike…. I can tell you that so many companies drive their business without fundamental data collection and analyze tools. As an example, how many times have you seen someone apply an algorithm to a data set without checking it for normality and these are statisticians or quality “experts”. Not to fault them, but everyone is so preoccupied with the end results that they by-pass some of the fundamentals.

This is a powerful indictment: “Managers feel compelled to generate data to show improvement.” Wow.

But why should we be surprised? It is entirely consistent with Deming’s 14 Points, especially #8 (Drive out Fear.), #10 (Eliminate slogans, exhortations, and targets for the work force.), and #11 (Eliminate numerical quotas for the work force and numerical goals for management.)

Maybe it is time to dust off your 1982 edition of Deming’s “Out of the Crisis”. We did not learn those lessons well.

And from Terri Jostes:

The 7 types of waste are now known as the “7 +1″ or 8 types of waste with the addition of “Creativity” or “Human Potential” as the 8th type of waste. All the wasted effort of overprocessing, rework and motion (in the form of moving data from one database to another) associated with the “data shuffle” causes our intelligent, highly trained, well-paid green belts and black belts to spend countless hours in unproductive, frustrating activity.

Why do companies allow this to happen? In some companies, it is seen as a rite of passage for a belt or a necessary, if unsavory, part of the job. Some belts even like doing this type of work - they’re good at it! Of course they are…they spend a lot of time doing it!

Evan’s right…It’s time to be strategic about our data gathering, compilation and analysis. In order to create a “data driven” culture, clean, reliable data has to be readily available to all levels of the organization. Letting the “data shuffle” continue in our organizations guarantees lost opportunity in our improvement activities and operational performance.

I love that idea: “Rite of passage.” Did you have to go through this rite? What is your story?

And from Forrest Breyfogle:

Evan, you indicated that the data shuffle is all the compiling, massaging, and manipulating data that you do to get something useful so that you can make “meaningful business decisions.” If the result was to make meaning business decisions that would be one thing and would be waste in that the analysis was not performed efficiently. However, it appears to me that the problem is worse in that often there is playing games with the numbers to make a situation appear better than it is… We need to blend analytics usage within an overall business governance system.

Excellent point: This isn’t just an efficiency issue; we need better governance. Can better data help that?

And from Terry Burton:

Today’s turbulent economy requires much more targeted Lean and Six Sigma efforts that produce an accelerated level of tangible results. That means a rapid and perfected “value-added” execution. We need to stop the data shuffle, and the training of the masses and put the money on the table - Or it’s all just another bandwagon! Too many organizations are stuck on this”mad belt” and “data shuffle” mode with their Lean and Six Sigma deployments.

One of the largest inefficiences we observe that compounds the data shuffle is that people are using multiple versions of the truth (facts). This is prevalent in organizations where the formal enterprise system has broken down, or where people struggle with their own personalized kluge spreadsheets to get (data shuffle) the facts. Some people tend to grab and shuffle the data that is available, rather than think through the specific data elements needed to solve the problem.

Think about the obvious. Not only are these folks inefficient due to data shuffling, but they all have different versions of the facts when they’re done! Now this leads to the wrong actions and firefighting, and the data shuffle becomes a viscious cycle. Their organizations would be better off if they made their “data shufflers” sit there and do nothing! Unfortunately, these organizations are not improving at the rate of the economy so despite all the belts, they are falling behind.

The largest challenge with Lean and Six Sigma is quickly thinking through and acquiring the right data to make the right decisions and get the right results. Some of our clients have reached this “utopia:” Real-time, visual event-driven metrics, a single version of the facts, decide-act-measure in real time. Based on true potential, we see that well over 80% of Lean and Six Sigma deployments are failing. People are hanging up the window dressing and getting their belts, there’s a lot of data shuffling and charts, but cultural transformation is not happening.

This economic meltdown is a great opportunity to rethink the “what’s” and “how’s” of your Lean and Six Sigma deployments and shift into a higher gear of new results.

Important concept: “A single version of the truth.” This reminds me of a conversation I had with a test engineer at an audio amplifier company who told me “In the past, if I wanted that data, I had to go mine it myself… People would be reasonably questioning my political motives for saying ‘We had 94% first pass yield last week. Now we have this standard called Hertzler, and you can go get the same data I just got…”

And from David Back:

I can only echo the points made and pass on some of my experience with management teams. Management by facts is a major change for many leaders and it is far more than setting up data cemeteries and then having specialist analysts or Belts providing insight in parallel to routine business processes. Managers need to buy in to the strategic nature of the change and be equipped with the clear concepts to act in this way. The size of this step is generally underestimated, old habits die hard ! It falls to all of us that understand this issue to promote the change at every possible opportunity.

“Data cemeteries…” What a great term.

And from Ken Place:

Although I agree that “the data shuffle” is a problem, I see more instances where data is just not available, what is available cannot be used, and new or additional data collection activity is required before an effective Lean or Six Sigma effort can/should even begin. As a Master Black Belt, many of my Black Belt students come to the first week of class ready to hit the ground running with a project. When we discuss the details of “Good” data they realize that they must return to square one and generate some history of the current state before progressing. Rather than massage the data to make it useful I find they must disregard current data and re-collect. Clearly non-value added but seldom fixed at the root of the problem, The Business Management System (BMS). In my opinion the BMS, formerly known as the QMS, should be designed with the correct, robust metrics in place for each process. Those metrics should reflect the health of each process as it contributes to the system, so that a company is able to asses where their next opportunity for continuous improvement exists. Without ongoing correct measures of at least efficiency and effectiveness, projects are not properly prioritized and work cannot begin right away. Yes metrics should be strategically established and available at any time for accurate monitoring, measuring and continuous improvement efforts.

At the risk of over-simplyfying, build the measurement system and the the rest will be easier.

What do you think? Is the data shuffle alive and well at your organization? How much time do you spend doing the data shuffle for your projects? Does the data shuffle undermine cultural transformation? You can leave a comment, tweet me, schedule a conversation, or call 800-958-2709.

Forrest Breyfogle posted a great question over at Linked-In:

Does our corporate leadership’s relationship-building strengths make it a challenge for them to truly understand and resolve the fundamental system improvement and re-engineering needs of the financial crisis?

From examination of the myers-briggs personality types we note that not everyone thinks the same. One observation is that some people tend to be systems thinkers and others are not. Systems thinkers, according to the Myers-Briggs Type Indicator [MBTI] manual, are those persons who have NT temperament and make up only 15% of the U.S. male population (female is less). My hypothesis is that high level government and business decision makers do not tend to be system thinkers because it takes a lot of relationship building to move upward. If this is true, many of our overall decision makers can have a very difficult time approaching the economic crisis as a system issue that needs process improvement/re-engineering. What are your thoughts?

I think Breyfogle may be on to something. I’ve taken the MBTI, and I’m an NT. I realize that I think differently from a lot of people.

What I’ve learned, however, is that ready access to real-time data helps people who are not systems thinkers see connections they would otherwise miss. That’s why having a good theory of data and making data more visible and accessible is so important. That is how you turn data into knowledge.

The follow-up comments are interesting and reveal a wide range of opinions about the underlying causes (and subsequent improvements needed) of the recession.  My own opinion?

What the MBTI doesn’t address is the question of values raised by some other commentators. Is the term ‘free market’ used in the way classical economists advocated: a market free from monopoly power, business fraud, political insider dealing and special privileges for vested interests? Or is it used in the more modern sense: free for predators to exploit victims without public regulation or economic policemen?

I own a small business and I don’t favor regulation, but I’m outraged at the way the marketplace has become free to enable Ponzi schemes and other scams to proliferate.

As a data guy and a systems thinker I would like to see us make better business decisions based on systems theory and data. But it has to be exercised in a free market that is fair and equitable, and that doesn’t reward theft.

What’s your personality type? Do you agree that it affects the way you view problems?  Which type of ‘Free Market’ do you advocate? You can leave a comment, tweet me, schedule a conversation, or call 800-958-2709.

A couple years ago we sponsored a research report by the Aberdeen Group on best practices in Six Sigma deployments. You can download a copy of the report, and a companion white paper that I wrote for the report called “Leveraging Technology to Transform Culture.” For me the most astonishing thing about that 2006 report was the disconnect between the challenges people say they face in their Six Sigma deployments and their responses to those challenges.

Most of the challenges people face are cultural:

Most people respond to those challenges directly by doing a checklist of initiatives: train employees, introduce change gradually, assign senior management as champions, engage outside consultants, steal talent from the competition, and so forth.

This frontal assault has been going on for years and it isn’t working. That’s the forehead smacking part of this.

Years ago I realized that making data more visible and accessible changed the way people look at themselves, the people around them, and the problems they face. Somehow just making the data visible takes away the personality and political dimensions - the cultural barriers - and helps people focus on solving problems.

Making the data very accessible - visually on the screen in a control chart or a dashboard - and making it available in real-time is a huge benefit. It breaks down all kinds of barriers.

My customer, Royce Binion, then Director of Operations at BAE Systems Controls in Fort Wayne, put it most succinctly when he said to me years ago “Real-time access to accurate, actionable data is the number one tool that has enabled us to move to a data driven culture.” This was way back in 2000 when his plant won the Industry Week’s 10 Best Plants award, and a few years before they would win the Shingo Prize.

This came up again for me this week when I attended a webinar hosted by the Aberdeen Group. They’re doing follow up research to see what has changed in the last 2 1/2 years, and they wanted to share their preliminary findings on best practices in Lean Six Sigma deployments. (If you’d like to participate in the study, you have until April 30. You get a free copy of the report if you do.)

What struck me as I heard this briefing is how little has changed. Cultural challenges are still at the top of the list, followed closely by IT and technology challenges. People still don’t seem to be connecting the dots.

Today I wrote to Cindy Jutras, the author of this research, to get her take on it. She wrote back:

in spite of all the data and IT related challenges from the previous slide (about the challenges people face in Lean Six Sigma deployments), there was not an appropriate response to those challenges. I agree that visibility is key. And our results support that. In general we found those with True Six Sigma have 110% better visibility than Industry Average and 580% better visibility than Laggards. Not surprisingly, they deploy far more IT tools than those not performing as well.

How about you? Are you using real-time access to accurate, actionable data to transform your culture? You can leave a comment, tweet me, schedule a conversation, or call 800-958-2709.

One of the discussion forums I try to monitor is Elsmar Cove. Sometimes it goes pretty geeky (I’m sorry, its just the word that comes to mind.) But sometimes it has some great questions. Here is one from that ‘Shesha’ posted today.

Hi,

Just wanted to know, what are the different methods you all had used OR are using to improve the Quality Culture in a organisation , mean to say to change the mindset of the people in a organisation towards implementation of process and Quality related stuff.

Thanks & Rgds, Shesha

I had to post the following response:

My experience is that when you want to change culture you have to provide the tools to make it so. Everyone talks about getting commitment from the top, and of course all that is true. But if that commitment is shown by table thumping and speeches and bands and banners it is a bunch of hogwash. (Pun intended - in reference to an earlier comment about how committed chickens and pigs are to preparing the farmer’s breakfast.)

If you want a quality culture that is data driven (which is what many people mean when they say they want a quality culture) the most important tool is the right data, in the right form, and right now.

Actually, this isn’t just my experience. The Aberdeen Group has published a couple research reports that put some dollars behind this. Best-in-class performers pay attention to building real-time data systems. Failing to do so undermines culture. And culture eats strategy for lunch.

You can download this and some supporting white papers from my website.

Four reports are especially on topic:

Aberdeen Event Driven Manufacturing Intelligence Report

The Role of Real-Time Data in Improving Profitability and Customer Satisfaction

Aberdeen Lean Six Sigma Benchmark Report

Leveraging Technology to Transform Culture

One of my staff members calls this “Evan’s Soapbox” and it is true.

CIO Magazine recently published a great blog post called “To Hell with Business Intelligence: 40 Percent of Execs Trust Gut“.

Based on separate research published by Accenture and Aberdeen, the post says that nearly half (40%) of major corporate decisions are based on ‘gut’ and not on data.

The number one reason? Sixty-one percent of the ‘gut deciders’ do so because good data was just not available.

Recently I visited one of these businesses. Ok, maybe they weren’t part of one of these studies, but they are a ‘gut decider.’ They’d love to do something different, but they can’t get to the data.

This company has an archaic, manual data management system. Every day they write down stacks of data on pieces of paper. They file (and forget) these in a filing cabinet. Some of it makes it into a homegrown (MS Access) data system.

Normal - busy - people can’t access this data.

But that’s OK, because nobody trusts that data that are there.  Even with Checkers checking the Checkers checking the people recording the data, nobody believes the data.  These people have no choice but to make almost all of their decisions based on gut.

In this situation, the obvious question is “So how’s that working for you?”

It was obvious to all of us that it isn’t working at all. How can I say that? Here are a couple of reasons:

• Customer complaints torpedo new business opportunities.
• High scrap rates siphon down profitability.
• Product returns clutter a warehouse, some of it retained as “inventory” for years.
• The list goes on…

Deciding from the gut is expensive.

I’ve found that when real-time, actionable data are readily available, people use it to make decisions - good decisions.

Of course these systems require an investment.  Of course people need training to make good use of data. But given the high cost of the gut, the return on these investments is phenomenal.

Having said all this, transforming into a data driven business is hard. As the CIO post states: “Losing that gut-first instinct isn’t going to be easy, and I’m not sold on whether companies can stomach the change required. ”

Lets hope they can. In this tough economy ready access to actionable real-time data may make all the difference in the world.

In the IT world what is classified as Business Intelligence may indeed be an oxymoron. But most of us need data - or more accurately knowledge - to make good decisions.

What do you think: Gut or Data? What is your experience?