No amount of technology will address the results of a poorly established or loosely followed process. Accurate analysis relies on clean data. Well defined processes result in clean data. A loosely followed process can result in critical missing data elements, which takes manual intervention in cleaning it up for analysis, wasting valuable time and resources.
Take, for example, the order entry process for a water-cooler manufacturing company that directly sells water coolers to businesses, and installs the product at the sites where the business is located. An invoice is given to the business at the time of sale. The invoice is generated from a Order Entry System with the minimal information required (Customer Name, Product Name, Sale Price, Discount, etc.) but information on the Sales Person(s) associated with the data is not always entered, as it is not “required” data.
Later, at the time of calculating commissions for the Sales Organization, gaps in the data will result. The person responsible for figuring out the Sales Commissions would be running pillar to post trying to figure out who to assign the missing commissions to, perhaps even manually manipulating incoming files for the Commissions report after making the right phone calls, to get it there on time.
Such situations do happen, and much as one would like to throw technology at them, technology is no substitute for tightening up the process that resulted in the situation in the first place, starting by assigning ownership for the process. I ran into a similar situation recently, and the importance of establishing strong processes and strong ownership resonated with me. I am normally not a process-centric thinker, but for once, I appreciated the need for it, as it resulted in data quality issues with a DWBI solution which technology alone just wouldn’t resolve.