Here’s a great example of a BI competency center (BICC) explaining and promoting BI to the rest of the organization. In this case, it’s SAP’s own BICC that created the video, destined for SAP’s 5,000+ employees worldwide. It was uploaded by Matthias Wild of SAP’s Global IT group (NOT marketing): BI4ALL in Plain English (but with a slight German accent ).

I love the use of low-tech graphics and great editing — and I’m sure this will increase interest in using BI internally within SAP…

You can hear more from Matthias and the goals of his team in this post on the SAP community network: The Concept of Business Intelligence for ALL (part 1 of 3)

I was asked this question last week at an internal meeting for the BI teams of a large Nordic telecom company, who had invited me to do a presentation on BI trends. Here’s my answer:

“It’s one where that successfully changes
the information CULTURE of the organization”

Business intelligence is about business and people, not information and technology. Information is useless unless you actually change something in the way your organization does business. And technology is useless unless it actually gets to the people who should be using it.

A truly successful BI program is one that not only provides value to the business with every project, but also inspires the company as a whole to push to the next level of information use.

I regularly present on the topic of best-practice BI, with topics like “Why BI Projects Fail and What to Do About It”, where I go through a long list of the BI problems I’ve seen repeatedly over the last two decades. In this post, I’ve extracted the top five that I think make the biggest difference in the long run:

1. Focus on Changing the Business

If you’re in charge of BI, your job is not providing a technical infrastructure, nor information, nor keeping internal customers happy – it’s using information to improving the way the company works.

BI projects aren’t delivered when you have built the data warehouse and started providing the reports to the business people – that’s just the start of the real project of changing the business.

Yes, of course the business people think that’s their job, but it’s the mindset that is important. Focusing on the end goal – even though you are not directly responsible for it – leads to the types of behavior that correlate to BI success:

• It helps you ask why people want information, and what they’re going to do when they get it – which in turn helps focus business people who may only have a vague idea of what they’re really trying to do, and what is possible
• It helps you learn and understand your company’s business
• It helps you prioritize projects, make the right tradeoffs, and dedicate resources more intelligently
• It helps you explain the value of your projects in business benefits, not just cost or productivity savings

As an example: somebody comes to you with a strong business need for better data, but the only way to achieve it is through manual information gathering and spreadsheets, and it doesn’t have anything to do with your existing DW or BI infrastructure. Is it still part of your business? Yes! (note this doesn’t mean that your team necessarily does the work).

You should be THE go-to person in the company that best understands both the business information needs and what’s feasible. You should be a clearing-house for best-practice “better run business through better information”, using whatever means are necessary.

2. Focus on People

The figures to the left came from a old IBM survey about IT in general, but ring especially true for business intelligence projects. We spend over 90% of our time on data and technology, while 75% of project success or failure depends on people, process, organization, culture, and leadership.

BI is a crucial interface between the tens of millions of dollars invested in your information systems over the years, and the people who are in a position to unleash some of the value in that investment.

Ultimately, BI projects never fail because of technology alone. Things go wrong all the time, of course, but it’s only if non-technology factors like leadership and expectation setting have been neglected that a BI project truly fails.

There are myriad signs that indicate underinvestment in people: the intended audience is disappointed with the solution(and IT replies “but that’s exactly what you asked us for!”); user adoption is systematically under-funded, with little ongoing training; executives don’t understand “why it all seems so hard – I just want these numbers!”; business teams end up downloading information into Excel because that’s what they’re used to; etc. etc.

If 75% of success is about people, why aren’t we spending 75% of our time on it? If your job is world-class BI, you should be spending a lot more time listening, explaining, evangelizing, and leading than you do “implementing”.

3. Provide Some Simple Data Access for Everyone

You must, of course, focus on the BI projects that provide the most value to your organization. B, but there’s one thing we have to learn from the consumer world: the most effective way to build demand for your product or service is to provide something that’s “too simple”, and then create a community around it.

For example, the iPod wasn’t the first MP3 player, it wasn’t the most advanced, and it certainly wasn’t the cheapest – but it was the simplest to use. And that’s why it’s the first MP3 player that most people ever heard of.

We design our BI implementations for our power users, and implement what they want – typically lots of complex data and “features”. Apple designed something for everybody, but keeping the number of features deliberately, even artificially low.

I’m convinced that Apple employed somebody whose job it was to say “no”: “Can we add some more buttons?” “No!” “Can we add search?” “No!” “Custom playlists?” “No!”.

Once the iPod was a success, more features were slowly added, and it’s a formula that Apple has repeated with newer devices like the iPhone and iPad – launching with fewer features than the competitors and aiming for volume first, and then extending.

The Web 2.0 world has followed a similar model: Facebook and Twitter did one simple thing well first, then built a community, then provided more features. Even video games follow this model. They start out easy: level one is about understanding the basic controls, and then you slowly build up skills level by level.

How does this apply to business intelligence? You should aim to roll out some simple analytic information to everybody in your organization – such as travel and expenses, or breakdown of mobile phone bills, or budget spending, or time management. And it should be incredibly simple to use – basic reports, with every fancy option turned off, and with no extra logon required.

Once you’ve done this (and promoted it widely), you’ll find that people soon come and ask for more information, other types of information, and more features. People get used to having information, their expectations get higher, and you’ve started changing the information culture from the bottom up.

Unlike rolling out BI to power users, widespread information to everyone sets up a long-term virtuous spiral of people accessing, using, and demanding information.

4. Tell Stories

Obviously, people need to believe in the benefits of BI if you stand a chance of changing the culture of the organization.

It’s notoriously hard to predict the return on investment on business intelligence projects, because “you don’t know what you don’t know”: having better information reveals new areas for improvement.

As a study by IDC showed, the majority of BI benefits are typically in “business process enhancements” which can be very hard to determine in advance.

By following #1 above, you’ll have a better idea of what the business benefits of your project really are, and be able to take credit for them (Sadly, if a Marketing VP, say, improves campaign performance thanks to improved business intelligence, they don’t often include a big ‘thank you’ to the IT organization when they tout their performance to the board)

But this can only take you so far. For all the insistence on “hard numbers,” executives – like the rest of us – are surprisingly anecdote-driven. Just as charities know that focusing on the plight of one child is more effective than a series of statistics, you need to be able to tell the stories behind the numbers. You need to collect real-life examples of how your projects have helped individuals in the organization transform the way you do business.

Here’s the crucial test: if you suddenly find yourself in the elevator with the CEO of your organization, do you have a compelling, 30 second story to tell about how somebody spotted something in the data (a risk, an opportunity, a problem), and was able to act on it? If you don’t, start researching how people are using the data you’re providing. I guarantee you’ll find a great story (and if you don’t, then you really need to rethink the foundations of your BI initiative).

5. Stick With It

With twenty years of experience to draw on, it’s not that the industry as a whole doesn’t know what best-practice BI looks like. But it can be very hard to put into practice.

BI remains a stubbornly complex, hard-to-simplify technological and business problem. It takes time, the environment is ever-changing, and there are no real silver bullets or shortcuts. Every successful project I’ve seen was the result of professionals doing the right incremental things day after day.

You have to roll with the punches and stay pragmatic. It’s not about having a perfect data architecture (nobody will ever achieve this). It’s about making endless iterative improvements, making the right painful tradeoffs, and picking yourself up after every business complaint.

If it helps, you should realize that while you only ever hear about the problems, business people do appreciate the power of the information that you’re providing. For example:

• According to a CIO magazine review, business executives are actually more likely than CIOs to believe in the importance of technology to the business(they just aren’t that sure that the CIO is qualified/able to deliver)
• Cindi Howson’s book on Successful Business Intelligence includes a survey that showed that 92% of business people said that BI had contributed somewhat or significantly to company performance (which was higher than the number of IT people that considered their BI projects to be moderately or very successful).

Ultimately, the best way to change the information culture of the organization is to lead by example, and being a tireless advocate for better run businesses. Good luck!

Today’s presentation at the Mastering SAP BusinessObjects conference in Melbourne, Australia is about implementing a BI strategy in your organization. Here’s the abstract:

Most organizations know that they should be taking a strategic approach to Business Intelligence. But what does this actually mean, and how do you go about doing it?

Using real-life examples of successful strategic BI implementations, we’ll cover key strategic themes such as fitting BI into your overall IT strategy, implementing BI competency centers and standards, effectively selling BI initiatives within the business, and using BI to align strategy and execution within the IT function itself.

• What is a BI strategy, and why is it important?
• What are the key areas to concentrate on when implementing a BI strategy?
• How can IT act as its own best reference, and use BI to improve its own performance?

You can download the presentation in pdf or ppt format, and you may also be interested in last year’s presentation about BI Competency Centers

The two-day event had a packed agenda, including great keynotes from Dave Rathbun of Integra Solutions (“To Infinity and Beyond”) and Peter O’Donnell, Lecturer at the Centre for Business Intelligence and Decision Support Research, Monash University (“Business Intelligence System Interfaces: The Good, the Bad and the Ugly”).

Photos of presenters: Dave Rathbun, Steve Bennett, Peter O’Donnell, and Ian Parker

I also particularly liked a presentation by Steve Bennett, formerly Head of Business Intelligence and Analytics, ING Direct Australia, (“Crystal Ball Gazing at ING Direct”), now CEO of the The Business Intelligence Group, and founder of the excellent Australia-focused BI blog “Oz Analytics.”

I delivered three presentations – click on the links below to go to separate blog postings about each, and downloadable copies of the files.

The Power of Business Intelligence to Transform the Way the World Works – with Ian Parker

BI Competency Centers: People+Information=Intelligence

Why Business Intelligence Projects Fail And What To Do About It

• Why have a BI Competency Center
• BICC Organization and Staffing
• BICC Functional areas and Key Tasks
• Creating a BICC
• Overcoming Common BICC Issues
• BICC Examples

The slides are available in pdf format (2.2Mb) and ppt format (4.6Mb) and are posted on SlideShare and Scribd.

The “tragedy of the commons” is a well-known issue in economics, involving a conflict between what’s good for the individual and what’s good for a group as a whole. Cindi uses it to describe the problem of departmental BI silos when it would make more sense to use a more enterprise-wide approach.

One problem with this example is that once you take all the variables into account, it’s not clear that silos are necessarily a bad choice, at least in the short term. My experience is that trying to take an enterprise approach too early is rarely a good solution in the real world, where it’s typically better to develop a series of departmental projects first, and only then go back and develop a more information infrastructure approach.

But I agree 100% that the “tragedy of the commons” does indeed plague business intelligence deployments. Luckily, the potential remedies are as well known as the problem – although they can be difficult to apply.

Put simply, economics is the study of incentives — and my experience is that misaligned incentives are one of the biggest issues facing business intelligence today (see related post on who “owns” BI issues)

To fix the problem, you have to assign ownership rights to the assets in question. For example, you can “enclose the commons”, and force people pay if they want to let their animals graze. The land doesn’t get over-grazed because people aren’t willing to pay to get access to land that no longer provides any nourishment.

By default, most organizations give ownership of their BI projects to the department that implements them — i.e. they have the “right” to create silos. This is the equivalent of farmers having the right to let their animals graze, and the opposite of the example above.

So one possible solution to our problem is to reassign ownership rights to a special body designed to get the best use of the organization’s assets — such as a BI competency center. If a department wants to build a silo application, they would have to “pay” the competency center for the right to build a silo — or at least explain why it was the best course for the business as a whole, rather than just their department. Note that this could still result in some silos being built, but only when the circumstances made sense.

However, having a central, “ivory tower” body controlling departmental activity is the inverse of today’s trends in decentralization. More and more organizations are pushing decision-making out to the organizations on the front-line, recognizing that the increased ability to react fast to new situations typically trumps the increased efficiencies of more centralized structures.

Luckily, in classical economic theory, you get optimal use of resources whoever gets ownership rights. So we can address the problem differently: departments can retain the “right” to make silos, and the BI competency center can “pay” the departments to do the right thing for the organization as a whole.

This solution is much better aligned with the way organizations typically work. The BI competency center get funding through a “tax” (e.g. the “IT infrastructure” line in the annual budgeting cycle) and provides expertise and resources to departments that agree to take a more enterprise approach.

Note that this situation allows for an “optimal” mix of silos and enterprise-wide solutions — if a department considers that they can build a valuable silo without the central resources, they’re still free to do so. By controlling the level of “tax”, organizations can exert more or less centralized control.

The problem is typically that organizations don’t think in terms of ownership rules, and fudge an incomplete and confusing mix of the two approaches, with some centralized control battling against the departments desire for autonomy, and disagreement about “what’s best for the company”. This in turn results in tension between IT and the business, further decreasing the likelihood of long-term BI success.

To summarize; First, it’s essential that organizations have a body that has the authority to represent the “common good” of integrated information — such as a BI competency center. Second, it has to be clear where “ownership” lies, and what mechanisms exist to “pay” the owner to do the right thing for the organization as a whole.