Chapter 7. Driving Change Effectively

With the advent of Big Data, the world has been changing over the past few years. In the preceding chapters, we discussed many of these changes and how to integrate them into your current organizational fabric. We talked about how companies can make sense of huge volume, velocity, variety, variability, and veracity of data and effectively visualize the analytics derived from this data. New organizational strategies and business models are being enabled by Big Data. Many management practices and beliefs are getting challenged.

Often, organizations make the mistake of considering Big Data a technology problem; technology here is a mere enabler. Embracing the true power of Big Data requires organizations to adapt to different thinking and behavior. Effective change management becomes crucial in such an environment. You need to transition your people and teams to the future state of business enabled by Big Data. In his HBR Blog on Predicting Customer's Behavior...

Understanding changes caused by Big Data

Leading Big Data thinkers such as Prof. Mayer Schoenberger, Alex Pentland, and others have been educating the world about some of the fundamental changes being caused by Big Data. The seven key ones are described in the following sections.

Correlation is leading to valuable insights without having to wait for specific causal analysis

Fast and effective processing of lot of data can now accurately predict what is going to happen next without understanding deeply why it is happening. So, the value of evolving data is taking precedence over static knowledge acquired through lot of hard work, perseverance, and significant investment in developmental programs. Prof. Mayer-Schoenberger remarks, "Correlations let us analyze phenomenon not by shedding light on its inner workings but by identifying a useful proxy for it."

This change requires organizations to develop new skills and archive some of the old competencies. For example, in earlier times, retail...

Applying the IMMERSE framework to manage change

Now, you have a good understanding of most of the changes in your world that Big Data is causing. Right away, the question is how do you take all of these changes and manage them for your business. There are many change-management methodologies and frameworks that you can adopt as well. Holger Nauheimer, a famed change management consultant and author, has created a collection of tools, methodologies, and strategies for change management titled The Change Management Toolbook, which is actually available for free download.

We have not found any specific ones developed for Big Data initiatives. We will now introduce a framework called IMMERSE to help you manage the changes. IMMERSE stands for Identify, Modulate, Mitigate, Role play, Educate, Show, and finally Effect; we believe these are the various stages an individual or a team has to go through in the change process. This framework is a progressive sequential one, which you should run in iterations...

Creating stakeholder groups to drive change

In your project team, you have a change leader. This person, as we have described in Chapter 5, Building a Winning Team, will act as your internal project team coach and also drive the entire change management program in your business. If the impact or span of the change is big, that is, if it crosses over multiple departments and involves hundreds of people, it will take more than a year to realize the benefits; we recommend that you create some stakeholder groups to make the change management more effective and pervasive.

We recommend that you do not create more than three such groups—a project group, work group, and review group.

Project group

This is your core project team comprising the various profiles we discussed in Chapter 5, Building a Winning Team. This team is primarily responsible for achieving the project objectives but should hand over the sustenance responsibilities to the work group.

Work group

The work group is the implementation...

Summary

In this chapter, we discussed the critical implications of having a robust change management plan for your Big Data initiatives because of the significant changes Big Data brings and the deep impact it creates on the business. The key changes we talked about are:

• How even without understanding the underlying reasons, it is now possible to predict outcomes by correlating data

• We do not need exact data to be able to predict future possibilities

• You can infer outcomes by looking at large volume of data, incidence of past events, and simulation of future scenarios

• You can analyze all kinds of data from all different sources at the same time without any inhibitions

• You do not have to be worried about normalizing data, that is, trying to define and interpret different types and sources of data from a common platform

• You have a very powerful asset in raw data

• You need deeper thinking about the risks and ethical issues with this massive data proliferation

We also understood that in most Big Data...