I'm continually amazed (and horrified) to see the annual BI maintenance and development budgets of clients that I visit. I think they are truly amazed themselves, and many times they wonder how they got to that point in the first place. It got me thinking about the parallels to automobile ownership. Did you ever have a car that you bought new, and then 5 years later you looked back at the cost of ownership of the car and said to yourself "HOW did I spend this much over 5 years on a single car?!"
Does the cost cycle feel like this?
Purchase price, warranty, add-ons, upgrades, repair parts, labor, tires, plugs, oil changes, parts, labor, towing, tune ups, new parts, recalls, repairs, labor, break job, tires, labor, etc...
It's likely you were caught in the complexity trap of cost. Some cars come off the line for $20k and cost you $5k to operate over 5 years. No real problem there. You have to expect some cost of ownership and maintenance. So why is it that many cars that cost $50k (new) will cost you an additional $30k just to operate over 5 years? Shouldn't they be even cheaper to operate, given the high initial cost? The problem is the complexity cost formula. It always prevails.
That which is more complex and requires greater specialty of skills will naturally cost more to maintain over time.
Think about it. Doesn't this same cost formula hold true for anything you own? Cars, houses, power tools. How about your company? Your government? It always holds true. That's why it's no surprise that this formula is at the center of the skyrocketing maintenance costs for traditional BI solutions. Here is the formula in its simplest form:
Cost of BI = (# of moving parts) X (# of specialty skills needed)
Using this formula, break down the BI solution(s) you already have, or even those you might be evaluating.
- How many tools are involved to get data from source to user? How many layers and processes does a column of data have to go through? How many repositories, databases, cubes, warehouses, data models, scripts and libraries does the data need to travel through to get onto a dashboard? These are your moving parts.
- How many specialty BI skill sets and software skill sets are needed to deliver BI with that solution? How many data modelers, ETL designers, DBAs, data architects, BI tool specialists, OLAP analysts, warehouse technicians, report developers, project managers and BI designers does it take to produce a dashboard or BI analytics interface? These are your specialty skills.
Multiply these together and you quickly get an accounting for those massive development and maintenance costs of traditional BI. The costs of specialty skill sets have gone up rapidly in I.T. over the past 10 years and will continue to rise. This puts great pressure on companies to either do less BI or to find a way to outsource some of the skills. If you haven't already seen this happening then keep your eyes open, you will.
The good news is that more and more companies are rejecting the tendency to add even more complexity and specialty to their cost formulas. This is helping bring about simpler, more powerful BI tools that can utilize traditional skills sets and business knowledge that are abundant in our companies today. Do the same. Be aware of the BI Cost Formula, and don't fall victim to it.