The age of data is upon us. In all facets of work and life, big data is changing what we know and how quickly we know it.
In business, “people analytics” is making headlines as the next big front in talent management and human resources.
Even so, analytics is not yet used to address some of the most pressing challenges leaders face. CCL’s Kristin Cullen-Lester and Phil Willburn say that it is past time for data science to burst onto the change management scene.
Business leaders should look to patterns, networks, and data science to improve their approach to change, they argue.
“A lot of consultants and leaders know they need to go beyond the formal org chart or hierarchy to drive change,” says Willburn. “But they go about it the wrong way. Modern workforce analytics can help leaders see how work actually takes place in their organization, tailor change efforts, and get it right.”
While working with organizations like Duke University School of Nursing and Mars Inc., both Willburn and Cullen-Lester have drawn on social science and data science to create an analytic approach to change.
“We use analytics — including network analysis — to see, map, and understand an organization’s patterns to answer the key question: How do things happen in this organization?” explains Cullen-Lester.
“Then the work involves connecting data with action to utilize existing patterns — or ‘nudge’ the organization to create new patterns — to achieve desired outcomes.”
This approach uses analytics to offer key insights, matched with targeted development actions, that are tailored to an organization and the changes underway. These analytics, insights, and actions focus on:
Understanding and using naturally occurring patterns in the organization to implement change. Horizontal and cross-boundary patterns of influence, information-sharing, and behavior are relatively informal, unstructured, and not obvious. They are the naturally occurring relationships that evolve over time as work is accomplished. These informal, natural patterns can be measured, analyzed, and visualized as networks.
Why does network data matter? Change must be executed through these natural working relationships because, when successful, change takes hold through and within daily work.
And, research has shown the type of network pattern impacts how easily ideas, opinions or behaviors catch on and the extent to which key individuals are able to influence others.
Organizational leaders must take the type of change into account to determine what they will be asking of others and how to best “roll out” the initiative. When leaders see and understand how information and influence flows in a function, division, or an organization, they are able make better decisions about change.
Finding, educating, and engaging change agents who can help accelerate the speed and expand the breadth of change adoption. Effective change agents are people who have a critical influence on change due to their position and role in the network — not by their position and role on the org chart. They are also personally receptive to change and have an interpersonal style that helps them influence others.
Change agents should also represent the workforce as a whole, representing different departments, diverse demographic groups, and complementary personalities. Organizations should then develop and support these informal leaders and influencers to build their personal capacity for change and engage in their role as change makers.
Change agents need to understand their own network, have an accurate view of the broader organizational network, and know the implications of these patterns of working for implementing change. Change agents also need to consider the change readiness of the people in their network.
These insights allow them to see ways in which they are well-positioned to scale change and when they may need to partner with others or build new connections.
“Both data science and complex change are here to stay,” says Cullen-Lester. “With accurate data and proven methods, leaders can break through the clutter of organizational change, gain clarity, and get results.”