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
Credits
Foreword
About the Author
Acknowledgments
About the Reviewers
Preface

Aligning existing initiatives


Aligning existing big data analytics initiatives in organizations is extremely critical. Parallel initiatives draw upon a lot of valuable organizational resources, creating stress for other projects. Moreover, executives and shareholders can sometimes get disillusioned and confused by the plethora of initiatives trying to do somewhat similar things, and in the process can become unsure about whether the initiatives will deliver the desired results. At an extreme, they might even consider big data analytics as yet another fad and wait for it to play out before taking any decisive action.

There is no magic bullet that can solve this problem. Every company is trying to figure things out in a manner suitable to their context and culture. If there are many initiatives running in your organization, it is a good thing—there are more people who are exposed to the power of big data and they are trying to solve many business problems using these capabilities. If they begin to collaborate, they can all learn from each other in using the technology and analytics better. They can also benefit from the new insights that interplay between the various initiatives present. This way, you may be able to reach answers to your business problems faster.

It is also critical to get some insights from data and analytics sooner rather than later. This helps to win the confidence of executives in the program; it also helps to continuously refine the results and insights.

You can take a very disciplined and collaborative approach towards aligning various big data initiatives in your company:

  • Make a list of all initiatives in the company that use data as the primary tool for a business outcome. These initiatives may not necessarily bear the big data tag, but you need to qualify whether the projects are using at least a high volume or high velocity or high variety data in its quest.

  • Identify the strategic intent of these projects. Find out what business outcome these initiatives are trying to influence.

  • Understand what is common and what is different between the approaches and outcomes of the different initiatives.

  • Classify initiatives into similar clusters of strategic intents of business outcomes.

  • Investigate whether the efforts of one initiative in a cluster can improve the performance of another initiative.

  • Differentiate activities around solving infrastructure issues and delivering user outcomes. The differences will usually manifest themselves in the different approaches. This step allows you to take another pass at spotting the differences and commonalities.

  • Find out how much investment each initiative is going to require and how long they are expected to last. You need to answer this question in the context of infrastructure development and outcome delivery.

  • Prioritize different initiatives, first based on expected benefits, then on required time, and finally on the basis of planned investments.

  • Create a map for most optimal initiatives geared towards achieving the strategic intent of the organization.

  • Secure executive buy-in for your strategic roadmap of the collated initiatives. When competing groups reach out to the executive team for their sponsorship, they need to support your roadmap and point of view.

  • Communicate your detailed research and the resulting map to the project teams. This will help them understand your strategic intent and align their interests and efforts towards broader and more impactful organizational goals.

  • Reallocate resources and investments based on this alignment. Establish a robust and fair governance process around the investments. We will talk more about this topic in Chapter 6, Managing the Money: Investment, Monetization and Performance Management when we talk about investments and financial management.

  • Review the entire process every six months at the latest. People will find new use cases for big data. Technical and financial barriers for pursuing such use cases are low. The proliferation of further initiatives is unavoidable and undesirable, so aligning them quickly is beneficial for your organization.

All the existing projects in your organization have most likely been initiated by some motivated individuals who see value in applying Big Data Analytics to solve business problems. In many cases, such projects may not have executive sponsorship and the project leader and team members are pursuing these as their labor of love to prove something new to the broader organization. Big data is often known to bring out entrepreneurial traits in people. Remember, people's passion and pain is associated with each of these projects. We do not want to discourage such behavior, but our objective is to channel their efforts and energies. The alignment exercise needs to be handled with care and compassion. We want the big data ecosystem in the company not only viable and valuable, but also vibrant.