- Kingland Platform
A six year old knows Indiana and India aren't the same.
Data management is one of the few disciplines where the state (population exceeding 6 million and known for the movie Hoosiers) and country (population exceeding 1 billion and more than 22 official languages) could be confused as being similar.
Let me explain. A client of mine noticed a hair salon transaction from India on a credit card statement. Unfortunately, the business manually entered India instead of Indiana - where he actually spent the money - providing a moment of frantic thought as he wondered if his information was stolen. Fortunately, he was able to laugh off the error because he works in the data sciences field and understood the challenges of data management.
But this leads to a potentially larger question – what causes data projects to fail?
Lack of executive support
Buy in from the executive team is essential. Senior leadership can serve as the battering ram that removes obstacles in your path OR the wall that prevents required actions from occurring. Depending on the approach to helping you succeed with the data project, the leader will understand the political climate, the influencers, and how to weave the 'why' of the data project into business outcomes for all stakeholders.
Doing too much manually
Most operational or compliance processes that require teams can be automated. This approach helps the operators, clerks, and administrators be more efficient - sometimes increasing efficiency by an order (or multiple orders) of magnitude. Can a twelve month project be reduced to a three month project? Can 10,000 hours of effort be reduced to a few hundred hours with the right tools? Automation can deliver these results. I’ve seen organizations that have created teams of 10-20 people to work on one data domain for a year only to have sub-optimal results. When you set aside the opportunity cost from that year of effort, the actual costs is hundreds of thousands, if not millions of dollars.
Going back to my friend above, what caused the India and Indiana problem? Likely, it was one of two issues. First, an operator failed to type in the right characters of the name of the company, or second, the system was designed with a maximum character length that forced truncation of the name. Two characters can change how your customer views the company and potentially how the company views your organization.
Resistant to change
Organizations and people are creatures of habit. We all channel our inner Frank Sinatra, singing “My Way”. The world is changing rapidly – new techniques, tools, and approaches exist today that did not a few years back. We must all learn how to change our approaches and look for new, more efficient and effective approaches. My colleague recently wrote about cognitive computing and what it could mean for you. Give it a read.
Where do I go from here?
We would enjoy hearing your stories of data project success or failures and share our prescriptions to help you move forward. Send me a message to talk further.