Why Big Data Needs Change Management

The combination of Big Data technologies and a smart approach to analytics can provide organizations with improved customer insights and a move toward data-driven decision making.  However, the keys to successful development of new capabilities include  both process champions and change agents to facilitate a smooth transition. Effective Change Management and Change Leadership are integral components of capturing the benefits of Big Data.

The Big Data Opportunity

Big Data provides an opportunity to leverage the convergence of technological advancements with the availability of a continuously expanding data universe to extract economic value from new and existing data stores.  This includes not only data in corporate systems and web sites, but data exhaust from social network platforms and the multitude of mobile and industrial devices – the internet of things.  In the case of both Business Intelligence (BI) and Big Data solutions, the overarching goal is to enhance decision making or provide new business insights.  The technologies or analytics themselves are not the full solution without understanding the use of data and analytics to make better decisions and support the evolution of the data-driven organization.

Data-Driven Organizations

Data-driven organizations adopt the leadership philosophy that aims to move decision making processes from instinct or intuition to evidence based.  Data-driven leaders consult the data when making decisions to foster a data-driven culture.  The end goal is not to replace human judgement in decision making but to augment business experience with hard information.  Analytics do not stand alone but need context and human experience to use in decision making processes.

Developing capabilities to support data-driven decision processes necessitates building an enterprise data infrastructure based upon company goals.  For analytics, this could include traditional BI approaches or integration of Big Data technologies – or some combination of both depending upon desired outcomes.  With either approach metrics and analytics should be tied to business initiatives and evaluated on business value and implementation feasibility.  For new analytics it is important to choose analytics that are both relevant and attainable.  Another important approach is to choose an Analytics Champion.  The Analytics Champion provides a bridge between IT and the business to educate, communicate successes, and ensure alignment with business goals.  While the Analytics Champion role is integral, it might not be sufficient for Big Data projects without the addition of Change Management and Change Leadership.

Change Management

Organizational Change Management is the process, structures, and tools to control change efforts and reduce or eliminate problems.  In addition, Change Leadership is needed to communicate vision and overcome complacency.  Change Management is the process and Change Leadership is the process champion.

Traditional BI technologies and approaches present a reduced risk when compared to Big Data implementations.  Business Intelligence solutions have the advantage of years of technology refinement, experience, and mature implementation models.  Big Data solutions show promise to deliver new types of analytics to the organization but cumulative experience and maturity of the technologies are not equal to BI.  New represents learning skills, processes, and most importantly change.  New can be daunting and naturally produce barriers to adoption.

Big Data requires both Change Management and Change Leadership for success.  Change Management focuses on stakeholder engagement, evaluation of organization readiness, facilitates training, and controls the change process.  Change Leaders craft compelling messages about objectives and drive awareness.  Change Leaders illustrate the use of analytics for business value and build momentum for enterprise change.  The idea is to focus on short-term wins in early phases, communicate value, and build on incremental successes to create data-driven decision making into the culture of the organization.

Conclusion

Organizations that develop and embed analytics into every day decision making processes are bound to experience transformation in organizational behavior that will benefit from a sound Change Management program to ensure adoption into the corporate culture.  While successful transitions rely on strong guiding coalitions, the role of the Change Champion/Leader is also key.  SEI has led successful change management efforts such as an HRIS implementation for a fortune 100 company affecting multiple divisions.  We understand that new technologies are disruptive and success does not hinge solely on the technology or the project team, but also the approach to Change Management.

Tim Eck

About Tim Eck