Deriving Usability from Big Data Conversation

June 19 2015

With so much hype going around for Big Data and Analytics, we come here to address this really “big” issue and to make out if this is really an issue or a “big” opportunity. There has been a lot of discussion on how to leverage the power of Big Data across businesses and transform operations to be intelligently driven by data; but still, the talk is just talk and the question is: How to really derive true value from it?

Deriving Usability from Big Data Conversation

There is still a GAP

In spite of the best efforts from giant firms like HP, Oracle, IBM and SAP, the bridge is yet to get strengthened. The data at the hands of the Original Equipment Manufacturer (OEM) often fails because they lack one main aspect which is the non-theoretical, practical view to own and manage the valuable information that is derived from Big Data and supporting analytics and tools. The amount of data that is generated on a daily basis or even minute to minute is enormous and until and unless you know how to best manage and utilize it, it’s absolutely useless.

Speaking of the Value

The major challenge in Big Data and Analytics is of deriving the value. No doubt that analytics and tools are essential for capturing and translating all the data into useful statistics. However, the money can only be made if we truly put to advantage the value derived from this Big Data and use it to address practical problems that a customer faces with the connected product in consideration.

The challenges of OEM

There are many challenges that an OEM faces as a part of value extraction.

  1. How to store this data churned out every other second?

  2. How to protect the data?

  3. What data is vital and what should be deleted?

The most crucial part of this Big Data process is that the data coming from the end-consumers can provide important feedbacks and useful insights on the working quality of product or application.

Is there a way to bridge this GAP?

There are open collaborations and partnerships that are helping OEMs fill this gap. They include giants like HP and IBM that are extending help to OEMs realize opportunities and tackle quality issues from the smallest possible design improvement to product usability and elevating customer experience.

HP in its briefing last year:

“We bring all data together in the middle to create connected intelligence to realize business value. It has been predicted that 90% of all data within the enterprise in the next few years will be machine and human information. Yet almost every tool that exists in the market today addresses only the business information. The ultimate strength of the platform we have designed is that we start with major problems and move inwards towards connected intelligence.”

This type of connected intelligence is priceless. Big Data that makes real sense to the OEM can be used to enhance product design and customize for each segment of end-consumer. In fact, it can bring about a powerful competitive advantage. This is because we are living in a digital world where data flow is extraordinarily smooth with every little operation of an enterprise, consumer or OEM. Intelligence and predictive analytics is becoming a requisite in industrial and manufacturing sectors and OEMs are required to work in a challenging business environment whilst struggling with continual shrinking cost set-up.

As such, true success depends on the OEM’s capability to turn ideas from the sketch board to a winning product launch and seek for proactive solutions to nullify the challenges created by design complexity and changing product requirements.