When it comes to data investment, data management is still asking the wrong questions and positioning the wrong value. The mantra of - It's About the Business - is still a hard lesson to learn. It translates into what I see as the 7 Deadly Sins of Data Management. Here are the are - not in any particular order - and an example:
Hubris: "Business value? Yeah, I know. Tell me something I don't know."
Blindness: "We do align to business needs. See, we are building a customer master for a 360 degree view of the customer."
Vanity: "How can I optimize cost and efficiency to manage and develop data solutions?"
Gluttony: "If I build this cool solutions the business is gonna love it!"
Alien: "We need to develop an in-memory system to virtualize data and insight that materializes through business services with our application systems...[blah, blah, blah]"
Begger: "If only we were able to implement a business glossary, all our consistency issues are solved!"
Educator: "If only the business understood! I need to better educate them!."
Many Indian CIOs and their infrastructure and operations (I&O) teams are in the market for a new data center as their existing data centers are running low on space, power, and cooling capacity. Forrester finds that data growth, virtualization, and consolidation are the main culprits behind these capacity challenges in India. For instance:
Data growth increases data center storage investments. Forrester estimates that storage consumes somewhere between 5% and 15% of the total power consumed in the data center and that the volume of data is growing by 30% to 50% per year.
Virtualization drives higher-density infrastructure architecture. Organizations face pressure to support more extreme compute densities and experiment with new infrastructure architectures.
Data center consolidation puts more pressure on centralized facilities. Per Forrester’s Forrsights Budgets and Priorities Survey, Q4 2012, consolidating IT infrastructure was a critical or high priority for nearly 70% of Indian IT decision-makers. This means more power, cooling, and space for centralized sites.
I recently took some holiday leave and saw two small, but clear examples of where mobility changes the economics of IT. The first was in a restaurant where the wait staff used their own smartphones and a simple order taking app. There was no expensive mobile platform for the restaurant to purchase in order to use this system. There was no expensive training program in place to teach the employees how to use the software. They simply bring along their own phone, download a free app to their device and start working.
The software is intuitive enough that any training required is done by their fellow staff members during shifts. What’s interesting about this example is that using mobile devices for taking restaurant orders isn’t new – but using employees own devices is. Previously, the expense incurred by restaurants having to purchase proprietary devices meant that only high margin operations could afford to use mobile order taking systems. And loss, theft or damage of the devices was not only expensive but also proved to be a sticking point for employer/employee relations.
The second example provides a sharp contrast. It involved a trip to a museum and the use of the audio commentary service. Though almost every visitor to the museum now has a smart phone device, an old proprietary hand held device was still in use there. This is an expensive option to operate for a low-margin business like a museum. There are now museums that have recognised this and offer apps on smart phones with capabilities well beyond what the previous dedicated hardware could provide. One such museum is the American Museum of Natural History. It not only uses the rich visual interface of the smart phone, along with the required basic audio commentary services, but it also reportedly helps the user navigate the complex campus using sophisticated wi-fi triangulation.