A post relating to this item from Finextra:
06 May 2009 | 8162 views | 1
Just a third of financial services executives think risk management principles in their business remain sound, with over half conducting or planning a major overhaul of operations, according to a surv...
Every day, I get email and snail-mail delivered faithfully, eagerly and hopefully into my mailbox by some organization that has spent time and money with the singular goal of delivering their message to little ol' me. They have either dedicated resources
or paid to find my name and my address. Unfortunately, these same resources haven't bothered to check to see if I am actually a good target for their product or service. Now the total value of the time and money they spent reaching me is neglible in and
of itself. However, if you multiply "me" by a few million, the wasted dollars, pounds and euros quickly add up. Data that doesn't hit your target audience or communicate with your current customers has a negative effect on your bottom line. This fact is a
universal truth among marketers. Now it seems bankers are getting the message too!
When you work in an environment that requires good quality data in real or near real-time to measure risk and accelerate decision-making, the costs can be significantly higher. With our interconnected and interdependent economy, the effects of poor quality
data can be staggering...just ask anyone who has looked at a balance sheet or 401K statement in the past 12 months. But as anyone who saw any of the three Terminator films, technology alone can't correct or fix flawed thinking.
Financial services organizations are going to have to make some tough decisions in an environment that is risk-averse and cash strapped. But you can't get good data if you're not willing to invest in the clean up. And you really can't keep good data without
spending to ensure that you don't pollute the water after you've cleaned up the oil. So here's a three step prescription based on the best fashion advice to help banks to begin the process of getting well:
1) Let go --Recognize that all of your data no longer fits your needs. Just like the beautiful dress I bought years ago is still beautiful, it no longer fits my style. Cyndy Lauper yes...me in 2009 not so much. Data goes out of style too.
2) Re-use--Every good fashionista knows that you invest in classic pieces. If you have a legacy system that still performs don't throw it away. Find a solution that allows you to add on new capabilities and extend its lifecycle.
3) Buy something new--Just like styles change, information technology and systems also change. In today's climate, good data requires flexibility. Can you add new fields easily, on-board customers quickly, react to regulatory change effectively?
Who knew? Fashion and IT problems could be solved with similiar thinking.