Failing Your Way into Business Intelligence Success

How often have Business Intelligence and Data Warehouse directors found themselves with a metaphorical gun to their heads? They’ve been given some version of this ultimatum: “we’ve spent millions on this system — we had better get millions in value out of it and fast, or you’re out on your ear!”

While it’s tempting to point to our vendors in situations like this, they can be our worst “frenemy” when it comes to these situations. They have partnered with our IT teams to design and pilot solutions in order to secure the business, and they indeed want us to succeed. But ultimately they have to move on to other clients. At some point they pack their bags, hand us the keys to the system, and collect their checks. It can feel a little like being wheeled from the hospital with our brand new baby in our arms — we don’t know much, but we do know that it’s up to us to make this grand venture work out.

This is where failure comes in handy. From that moment on, when the consultants get in their rental cars and drive back to the airport to fly home, we’re the ones making the system generate positive value in the organisation. No one says it, but we are guaranteed to fail. The key in this situation is to recognise and embrace this. It’s safe to say this because Business Intelligence is unlike other aspects of IT service delivery. It is at its core about the discovery of new business insight, identifying and leveraging data to open new gaps between what a company does and what it can do. And unlike other aspects of IT, failure is not to be expected, it’s to be celebrated.

Failure in BI is not about the technological challenges of connecting systems and routing data flows. Though those certainly do happen in even the most successful of implementations, the real failures come in the necessary lack of knowledge that informs early choices — choices that must by their immaturity be adjusted as the process of deploying and leveraging business insights grows. If we knew exactly how to build our Business Intelligence stack so that it was completely successful from the get-go, we’d already know what metrics are the most important, what dimensions provide the greatest insight, what data channels are value-add and which are noise. In short, if the implementation was completely successful, we didn’t need it after all.

This just sets up the premise though. The game-changing revelation is that the organisation’s real value derivation from BI is not in the technology. Instead it’s in the manner in which the BI ethic is woven into the fabric of its user constituency. And that means that its user and sponsors have to embrace BI’s facilitation of failure. Just as for Thomas Edison, each discovery of an unsatisfactory material eliminated one more candidate for the most effective lightbulb filament, each data revelation “failure” signals an unprofitable avenue that can be abandoned with a clear conscience.

Don’t misunderstand though, some of these revelations can be costly ones: discovering that an appliance solution is premature for the business to adopt and leverage is good news, but sponsors don’t like hearing that after they’ve already signed the checks. The hard work of the BI Architect or BI Director sometimes comes down to navigating the difficult balance between fostering a culture in which BI can flourish in its most essential way — allowing us to stumble sometimes haphazardly into data-driven business value, while at the same time anticipating and avoiding costly dead-ends before the organisation has committed too fully to them.

DataHub Writer: Douglas R. Briggs
Mr. Briggs has been active in the fields of Data Warehousing and Business Intelligence for the entirety of his 17-year career. He was responsible for the early adoption and promulgation of BI at one of the world’s largest consumer product companies and developed their initial BI competency centre. He has consulted with numerous other companies about effective BI practices. He holds a Master of Science degree in Computer Science from the University of Illinois at Urbana-Champaign and a Bachelor of Arts degree from Williams College (Mass)..
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Failing Your Way into Business Intelligence Success

How often have Business Intelligence and Data Warehouse directors found themselves with a metaphorical gun to their heads? They’ve been given some version of this ultimatum: “we’ve spent millions on this system — we had better get millions in value out of it and fast, or you’re out on your ear!”

While it’s tempting to point to our vendors in situations like this, they can be our worst “frenemy” when it comes to these situations. They have partnered with our IT teams to design and pilot solutions in order to secure the business, and they indeed want us to succeed. But ultimately they have to move on to other clients. At some point they pack their bags, hand us the keys to the system, and collect their checks. It can feel a little like being wheeled from the hospital with our brand new baby in our arms — we don’t know much, but we do know that it’s up to us to make this grand venture work out.

This is where failure comes in handy. From that moment on, when the consultants get in their rental cars and drive back to the airport to fly home, we’re the ones making the system generate positive value in the organisation. No one says it, but we are guaranteed to fail. The key in this situation is to recognise and embrace this. It’s safe to say this because Business Intelligence is unlike other aspects of IT service delivery. It is at its core about the discovery of new business insight, identifying and leveraging data to open new gaps between what a company does and what it can do. And unlike other aspects of IT, failure is not to be expected, it’s to be celebrated.

Failure in BI is not about the technological challenges of connecting systems and routing data flows. Though those certainly do happen in even the most successful of implementations, the real failures come in the necessary lack of knowledge that informs early choices — choices that must by their immaturity be adjusted as the process of deploying and leveraging business insights grows. If we knew exactly how to build our Business Intelligence stack so that it was completely successful from the get-go, we’d already know what metrics are the most important, what dimensions provide the greatest insight, what data channels are value-add and which are noise. In short, if the implementation was completely successful, we didn’t need it after all.

This just sets up the premise though. The game-changing revelation is that the organisation’s real value derivation from BI is not in the technology. Instead it’s in the manner in which the BI ethic is woven into the fabric of its user constituency. And that means that its user and sponsors have to embrace BI’s facilitation of failure. Just as for Thomas Edison, each discovery of an unsatisfactory material eliminated one more candidate for the most effective lightbulb filament, each data revelation “failure” signals an unprofitable avenue that can be abandoned with a clear conscience.

Don’t misunderstand though, some of these revelations can be costly ones: discovering that an appliance solution is premature for the business to adopt and leverage is good news, but sponsors don’t like hearing that after they’ve already signed the checks. The hard work of the BI Architect or BI Director sometimes comes down to navigating the difficult balance between fostering a culture in which BI can flourish in its most essential way — allowing us to stumble sometimes haphazardly into data-driven business value, while at the same time anticipating and avoiding costly dead-ends before the organisation has committed too fully to them.

DataHub Writer: Douglas R. Briggs
Mr. Briggs has been active in the fields of Data Warehousing and Business Intelligence for the entirety of his 17-year career. He was responsible for the early adoption and promulgation of BI at one of the world’s largest consumer product companies and developed their initial BI competency centre. He has consulted with numerous other companies about effective BI practices. He holds a Master of Science degree in Computer Science from the University of Illinois at Urbana-Champaign and a Bachelor of Arts degree from Williams College (Mass)..
View Linkedin Profile->
Other Articles by Douglas->

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