Apr 4, 2012

The Dirty Little Secret of Tech BI Successes

“98% of companies declare their BI initiatives successful on week 1, yet less than 50% of them remain successful by week 10’ BI Valuenomics & Gartner

Just a few months ago stepped into a BI project only to be told still again that ‘Our BI project was an IT success, but a Business Failure’, which got me right back on the need to push away from the current belief of ‘Technology is King’ and move towards Gartner’s recommendations of ‘Without business in business intelligence, BI is Dead’. There are three ways to look at this dilemma in Business Intelligence worldwide.

On one side, our first category of customers,  of the equation are the mega corporations with seemingly unlimited resources and budgets. They have their pet vendors, will only deal with them and are willing to go through tens of cycles and as many lessons learned sessions while they continue to travel along the same path desperately hoping for a different outcome this time. These corporations have a blanket order for their global BI initiative with prime vendors. The belief with these corporations is that good quality must cost more, and thus spend many millions of dollars per annum of their BI initiatives alone. Their continue with a string of IT success and business failure deployments, followed by a long lessons learnt initiative, followed by still another round of ‘lets get it technically right this time around’ approach. For these corporations I would like to state that in our flattening world where efficiency is the prime competitive advantage this advantage could slowly erode not only your budgets but also the decision making capabilities of the executives therein. No corporation has infinite resource for infinity – not if it is underutilized consistently. (Probability of occurrence 3-5%)

The second category is medium to large enterprises that have resources but would like to utilize them optimally. These enterprises bid competitively and try and negotiate the lowest cost partner with the highest quality perceptions. What the companies often get is lowest cost associated with lower skills than what their business should have got. Low skills often result in misaligned roles:skill selection, which in turn results in a higher degree of technical only solution. These resources will only be able to give you what your business demands and if your business does not know enough they will only demand what they have, and that could be a waste. The belief in these companies is that quality can be maintained despite getting lower and lower skilled resources (due to cost restraints). These companies often miss both the IT and business goals, but more often meet II goals and miss business expectations. For these companies it is critical to get a solid BI Business Value Architect that works with the business owner and steering committee members to guide them to accurate decisions. It is recommended to first conduct an alternative analysis followed by the decision that the analytics are enabling- and not simply in replicating reports. These companies have a more than 50% rate of failure followed by desperate unplanned spending often as lower rates than even before. (Probability of occurrence: 80-85%.

The third category could be any company that have an unbending faith, very much like the category 1 customers but for different reasons. These companies bid competitively and then leave everything to the technology vendors to solve and deliver. What these companies get is a lot of content and reports but very little business alignment or reports that truly meet business expectations. These companies want to deploy a solution in the fastest time, with the least business contact and the maximum technology solution. They get what they demand. The belief in these companies is that standard best practice delivered content should be able to meet their needs – only to find out that in reality it never actually can. The belief in these companies is that the highest quality comes from minimum customization and maximum standard reports. In these companies IT always meets its goals and business rarely if at all. For these companies it is critical to point out that standard business content very rareluy meets business expectations other than for a few specific objects. It is recommended to let business view not just the title of the reports but also the content of each report being delivered. These companies have an over 70% probability of failure and that is optimistic. These companies almost always wonder if BI is a worthwhile investment. (Probability of occurrence 10-17%)

When customers launch their BI projects they often imagine a smooth journey with geniuses taking them to their promised land. However in over 50% of these BI projects we find that they are filled with crushing defeats, near-death experiences and very low user satisfaction. All this leads to rush order of unplanned projects.

When we look at some of the most successful BI implementations we consistently find a high level of business participation in these projects. Evidence substantiates that BI success is directly proportional to the participation by actual business stakeholders. In almost every case these were business lead and owner BI project. (Probability of occurrence Under 50% according to Gartner)

On the other side of the coin we have the most unsuccessful companies and in these we find project teams that shun business participation and assume they are already at the pinnacle of their deliverables. Unlike in successful projects there is little option to accept defeat or throw in the towel in these cases for three reasons. The first is that if you do you will lose your job. The second is for most companies it is very difficult to state that we just blew $4 million on a badly planned project. The third is that after the BI spends there is still pending business expectations that need to be fulfilled. All this leads to disruptive unplanned projects that rarely do the right stuff the second time around. (Probability of occurrence over 50% according to Gartner)

BI deployments should not be like UB-40 or the 40th attempt that actually succeeded. We need to get this right the first time and right now we have enough scientific data to achieve this goal.  As an executive if ou have a mission to succeed then you need to take ownership and accountability for its success – do this with scientific principles behind your back and not technocratic assumptions.

So plan your work and only then work your plan can only succeed – as that leaves failure absolutely  no option.

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