There has been a lot of buzz about Big Data.
It is claimed to be the next frontier of innovation, competition and
productivity. It is a growing torrent..!! Lets see whether there is dearth of
evidence for all these claims. Per a recent research by McKinsey, 30 billion
pieces of content are shared on Facebook every month. Around 40% project growth
in global data generated per year compared to 5% growth in global IT spending.
Approximately $600 billion is the potential annual consumer surplus from using
personal location data globally. Around 60% can be the potential increase in
retailers’ operating margins possible with big data. Per IBM recent report, 90%
of the world’s data was created in last 2-3 years. This is just the tip of the
iceberg – of the amount of data we have and the potential it has.
Big Data and analytics actually have been
receiving attention for a few years but the reason of discussion is changing.
Earlier companies used to think how to get the relevant data and use analytics
to make sense of it. Now, companies see that their competitors are exploiting
the data and they are left behind. Companies get many advantages from using
data and analytics – how they improve in pricing, how they can offer better
customer-care, how they can improve in segmentation and how they can optimize
inventory management. The key is to focus on the big decisions for which if the
companies had better data, better predictive ability, better ability to
optimize, they would make revenues/profits. There is no point of mining data
where it would not fetch worth revenues or profits.
Key success for exploiting data analytics
comes down to three things – data, models and transformation. Data is the
creative use of the internal and external data to give a broader view of what is
happening in the organisation (e.g. operations, customers, marketing, sales,
etc.). Modeling is using this data into workable model that can either help
them predict better or allow optimizing better in terms of business. Finally
transformation – is about enabling the company to adapt the company to take
advantage of this data in models – such as using tools for managing and
monitoring. For implementation, companies need to have people who have sense of
business as well as understand analytics else they will end up making naïve
business decisions. Besides, companies need to focus – meaning do not try to
change several things at once rather just try to and focus on 2 or 3 things.
Analytics can help companies synthesize data
into insights – help in key decision-making, thus increasing revenues and
profits. In top performing companies, analytics have replaced intuition as the
best way to answer questions about what markets to pursue, how to configure and
fix price-offerings and how to identify where operations can be made more
efficient in response to cost and environment constraints. Many business
leaders are anxious to capture the benefits of new intelligence but they need
to take analytics the full distance. Top companies are enacting their business
analytics and optimization vision, making it possible to operationalize
decisions and optimize business performance across the enterprise. To achieve
this, they are using various tools, effective governance. Driven by
intelligence, companies can better anticipate supply chain constraints and
competitors’ countermoves. A focus on driving change – in people, business
processes, in organisation structure and management systems – has the greatest
impact on achieving breakaway performance.
This is the time when organisations should
institutionalise data-driven decision-making rather intuition and harness Big
Data. To find the ways that are most appropriate for a given company, leaders
need to figure out how the company’s data might address specific business
needs. But three of the ways that every organization should think through are:
• Creating a data-driven culture
• Informationalization
• Big data/advanced analytics
Putting data to work requires changes in how companies typically operate when it comes to data. It takes a laser focus on data quality, disciplined data-management, the right talent and a facilitating organizational structure. These are, certainly, the business imperatives if the companies do not wish to be left behind in the era of Big data and analytics.
