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Intelligent data-driven change management

Blog: Capgemini CTO Blog

In the past, the purpose of detailed planning was to define the target state, scope, and direction that a transformation would take. Today, transformational initiatives have become increasingly dynamic, continuously evolving, with an unpredictable trajectory that is influenced by multiple feedback loops coming from customers and employees. It has also become the norm for companies to concurrently run multiple initiatives that often cover a wide spectrum of themes, from customer journey innovation to exploiting the value of data to introducing new technologies.

Human beings are not equipped to rapidly adjust to the constant alterations in processes, tools, roles, or ways of working. Actual numbers highlight the need to focus on the employee, who is the primary change driver, while keeping an eye on simplifying technologies:

Organizations should focus on a human-centered design approach to transformation, augmented by data and AI. We call it “Intelligent Data-Driven Change Management (IDCM).”

  1. Using data to unlock new value

We see change management evolving towards IDCM, which is at the sweet spot of human capabilities and data insights. IDCM combines the unique strengths of human emotional intelligence, such as business acumen, empathy, the ability to manage conflicts, and the power of inspirational leadership that influences others with actionable, insights-enabled by algorithms.

This new discipline will require a new type of digital platform that goes beyond digital tools as we know them today. It must put people at the center, empower them through AI-driven recommendations to improve, and maximize their impact on the transformation.

Moreover, in today’s world employees expect a consumerization of their employee experience. It is proven that this kind of personalization, e.g. of learning, boosts employee engagement as the level of relevance correlates with their interests and they can see their fact-based contribution to the transformation.

Data can finally be a fact-based evidence to map and benchmarks the maturity of capabilities and the ability to drive change within different parts of the organization.

While the data-driven component plays a crucial role, the human aspect behind change remains critical for organizations. Humans are social beings and will always be motivated by others, for instance leaders who inspire them and are able to set a vision while mobilizing the right stakeholders to drive change.

  1. Creating business impact with Intelligent Data-Driven Change Management

InsideBoard, a startup in which Capgemini Ventures recently invested, offers such an employee-centric environment in the form of an AI software-as-a-service (SaaS) platform. Its platform enables organizations to boost technology adoption and business transformation projects by connecting employees, measuring their individual progress, and increases their engagement by recommending targeted content. Its analytics and AI functionalities monitor and manage emotional intelligence to facilitate change.

Recent projects and metrics prove that tangible and substantial business outcomes can be achieved by adopting Intelligent Data-Driven Change[1]:

Our experience proves that mature solutions such as InsideBoard are ready to be deployed and to generate a business impact at scale through:

  1. Getting started

Rolling out an intelligent data-driven change management platform such as InsideBoard happens in iterative steps. The starting point is a pilot project that will prove the proof of concept, technology, and business benefit for the initiative.

A gradual scaling to aggregate the data of a wide range of business applications, metrics, and contents is possible and will amplify the benefits for organizations.

[1] Figures based on InsideBoard experiences.

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