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Buying business intelligence (BI) software can be hard & frustrating - especially with technical evaluations, prioritizing requirements, and funding. When I underwent similar "rough patch" when I had to buy a BI software, one thing quickly came in my mind - is there a checklist that I can use to make my life simpler? So once I got through that task, I sat back and started preparing a list of pointers that a buyer should look into while buying any BI software.
1. Return on investment (ROI)
ROI is the king. It's the most important factor because it's the bottom line! We don't implement BI systems because they are trendy & sophisticated. We invest the company's "hard earned" money in a BI system with the most important motive - getting more money back from the system than what is invested, in terms of savings (cash or kind, you know). All the remaining points somehow depend upon the ROI.
2. User requirements
There's no point building any system unless it delivers what the users want out of it. So it would be a valuable investment when you carefully jot down the requirements from business users & stakeholders.
3. Ease of use
Traditionally, BI systems have been difficult to implement, set up, understand, drive – everything about them has been hard: I call it "rocket science". However, the systems now are becoming more user friendly & easy to drive. This parameter is extremely important because finally the end users should find the system useful otherwise all the money invested goes in drains... Give serious consideration to ease of use for the end user, but also consider that the easier it is for your technical staff to build and deploy a BI system, the cheaper it will be to implement.
4. Killer functionality
It may be that one BI software product alone offers a single piece of functionality that outweighs virtually every other consideration except ROI. You'll know it when you see it (or your IT team will tell you about it). But please remember that sometimes one killer feature makes the whole investment worthwhile, as opposed to trying to get another product to do something that it really wasn't designed to do.
5. Data volume
How much data do you have - and how much will you have in the future? It depends upon the business you're in, historical data in your business, future prospects, and a little forward thinking. Certain BI technologies do not scale well! Some data mining algorithms, for example, may work well with a million rows, but with 10 million rows, they may run like a (slow) dog. Try to gauge data volume accurately and match it to software/hardware capabilities. Then make the vendor really prove to you that the software can handle it.
The hardware available for BI covers a huge range:
- Commodity standalone boxes.
- Commodity boxes bolted together to form Massively Parallel Processing (MPP) arrays.
- Dedicated MPP machines.
Costs vary accordingly. If you under-specify the hardware or try to use the wrong hardware for your new BI software, your system will never perform optimally and the ROI will fail to appear.
The business intelligence software buying points that you should not consider:
Cost isn't important - BI systems are costlier than other software; it's return on investment that counts. It's better to invest $5 million and reap $30 million than to invest $2 million and reap nothing. Spend enough time to calculate ROI that you anticipate from this BI system and go for it... forget the cost!
8. Current source systems
Existing operational systems such as the finance, CRM and human resources systems are typically underpinned by a database engine. Just because you're using Engine X for transaction processing does not mean you have to use it for the new BI project, for the simple reason that the Extract, Transform and Load (ETL) tool essentially sits as a buffer between them. Any good tool will be perfectly capable of extracting data from any number of different source systems and transforming it into any flavor you like. This doesn't mean you should ignore the existing expertise in your company; but, in terms of functionality, there is little need to consider the existing engine.
9. Sales pitch
Most of sales pitches are actually misleading and overvalued. I would strongly urge to patiently listen to these sales pitches, get back to pen & paer, do your home work, understand what your requirements are, accurately calculate ROI, and then make a decision. Let the sales pitches be where they are supposed to be - in the board room. Don't allow them to go into your heads. :)