Book Image

Making Big Data Work for Your Business

By : Sudhi Ranjan Sinha
Book Image

Making Big Data Work for Your Business

By: Sudhi Ranjan Sinha

Overview of this book

Table of Contents (15 chapters)
Making Big Data Work for Your Business
About the Author
About the Reviewers

Identifying the strategic implications

To understand strategic implications, you first need to understand the current role of data in your business. In order to help your understanding, you need to explore answers to four key questions:

  • How many of the data elements are currently being used to influence your existing revenue and profit streams? Today, most of your considerations may be usual financial data related to P&L or balance sheet items.

  • What is the contribution of your organization's data elements in the revenue and profit streams?

  • What capabilities and business models do you have today to use the data?

  • What capabilities and business models do you need to build or acquire to use the data?

Answers to these questions will lead you to areas that may be blind spots for your organization today in terms of both opportunities and threats. For example, in the previous example of the water purifier manufacturer, if you do not use maintenance records as a consideration in your revenue strategy, the implication is that you are possibly not exploiting a new maintenance model or replacement part sales opportunities, or even that somebody else might start doing it.

Let us consider another example. Anita has been banking with one particular bank for over 16 years and is extremely satisfied with their services. For all these years, she held salaried jobs and (thankfully) her salary grew several times. In addition to savings accounts, she has engaged in other types of transactions with this bank—all experiences were very satisfactory. However, recently she realized that this bank has handled less than 20 percent of her money. The bank did depute competent and nice managers to attract her business, and provided impeccable customer service to build credibility. They missed out on tracking her over the past 16 years across their various divisions to meet her needs of the hour. They had all her data, but used a quarterly savings account balance to pursue opportunities with her. This is another example of failing to understand strategic implications of data and analytics.

The problem is not the availability of data; it is appreciation of the value of data and what it can do for the business. Comprehending the strategic implications will lead you to conclusions that are not explicitly stated or obvious at a casual glance.