While digital data is practically doubling every two years (according to IDC figures), only a small percentage (1 to 5%) of the data available from a single company is actually being leveraged to better manage the business.
Fundamentally, it’s the complexity (and the cost and the time) of doing it. Fortunately, the new Big Data wave is reshaping this scenario by enhancing the technology to store, integrate, and analyze larger and heterogeneous data sets faster, cheaper, and simpler.
Breakthrough innovation and empowerment
Access to information will reduce the need to queue in the IT and other departments. Individual departments will have the power and the freedom to develop their own business intelligence platforms, self-serving the insight they need to answer their own questions, while keeping the related technology protectively hidden within the IT unit (eg: data architecture, security, etc). Thus, this “democratization” will add the needed speed, flexibility and effectiveness to better manage a business.
Sounds great. And it is actually. But as with all breakthrough innovations, this requires business leaders learn how to effectively manage the new scenario before simply embracing it.
Look back to look forward
Looking at the past, a similar trend came with the first surge of the business performance cockpits. Do you remember few years ago? How many cockpits did you have? How many have you seen running within your company in the last years? What was the cumulated cost behind (if anyone was even able to monitor)? How many were similar and overlapping? How many really added value?
My Three Principals of Information Management
As businesses move their centers of gravity towards the business users, the department leader must ensure wise management of its new information.
Use my three principals to guide you:
1. Need. Avoid jumping on the trend of creating your ‘own’ business analytics from scratch. Scout other sources first. In most cases, someone else already has some at least pieces of the analytics you desire. Duplications create hidden costs and information inconsistency within the company. Don’t recreate the wheel if you don’t have to.
2. Understanding. Verify that the people in your unit have a deep business understanding of the data to be used. Raw data are often misleading if not properly cleaned and adapted to the specific context.
3. Value. Challenge the value of the analytics. Always. Even if it appears cheaper and cheaper, there is still has a cost attached.
Dramatic business data expansion is clearly upon us – providing dramatic and democratizing impacts. Yet, as Eleanor Roosevelt once said, “with freedom comes responsibility.”