The need for effective change management tools has never been greater. The COVID-19 pandemic has already impacted people, health, businesses, stock markets, and other global economy pillars. For organizations, this means a new normal. The uncertainty derived from COVID-19 requires organizations to recognize employee and leadership sensing and intuitions to deal with business continuities (e.g., Hallin, Andersen, and Tveteraas, 2017).
The COVID-19 pandemic can be summarized through the following uncertainties:
Along with the COVID-19 crisis and its uncertain impacts, organizations face a fourth industrial revolution characterized by a tremendous digitalization and computerization increase. New technologies and data sources include collective intelligence (CI), personal connected devices, big data, machine learning, artificial intelligence, the internet of things, and blockchain technologies, to name a few of the most dominant technologies.
We live through a time when lines between the physical, digital, and biological spheres become blurred, resulting from the new technologies. The fourth industrial revolution has a significant impact on all disciplines, industries, and economies, disrupting almost every industry in every country and creating massive changes at unprecedented speed. That is why many organizations have already started to invest in the digitalization of their business models.
To continue to adapt organizations rapidly to "the new normal," organizations need effective change management processes that can help organizations thrive in turbulent times (Cullen, 2018). In the "new normal," where change is the new constant, collective intelligence technologies can successfully bring organizations through change processes.
Collective intelligence is the knowledge that arises when people join forces, collaborate, and work together to make decisions. It is a shared knowledge harnessed through new crowdsourcing technology. While artificial intelligence relies on machines, computers, and/or software systems, collective intelligence relies on people. In our day to day life, artificial intelligence is text-prediction in emails, content suggestion in Netflix, or traffic prediction in Google Maps. On the contrary, collective intelligence is the shared intelligence of multiple people's insights, ideas, or solutions – it is the sum of human knowledge (or of a specific community) on a given topic. When collective intelligence is combined with artificial intelligence technologies, we can amplify the value and effect of such systems and provide organizations with powerful and relevant tools for navigating uncertainty.
While the implementation of new technologies is essential to adapt to a new reality, many organizations fail to realize that transformations require a considerable investment in the people using the latest technologies. Ignoring the people dimension in any change process can increase costs and the risk of the change not being implemented successfully. The change process will be wasted if people who should change do not adapt to the change.
Ten years of correlation data from over 2,000 data points show that initiatives with excellent change management are six times more likely to meet objectives than those with poor change management (Prosci.com, 2018). McKinsey data also shows that the return on investment captured from excellent change management is significantly more than poor change management. That is, when a change of direction is used effectively on a project, it can dramatically increase the success rate of the effort (McKinsey and Company, 2020).
Change is difficult as it always implies adapting to uncertainties. It is not possible to remove uncertainties or the variability associated with change processes. Project management searches to mitigate risks and uncertainties in change processes by providing direction on sequencing milestones, deliverables, activities, and resources over an effort's lifecycle. However, these activities are only mechanisms to control the deliverables in a change process. Unless organizations proactively harness employees' knowledge and intuitions during the change process, management cannot know if they are on the right change path and provide employees with the preparation, support, and skills they need to embrace the change.
Collective intelligence technologies can provide the foundation to harness the insights and intuitions from employees in lead time, in many instances, 3 – 6 months in advance during change processes. Such a lead time will be enough for management to receive insights about risks in time to adjust the course of the change processes with their employees' predictions. In every organization, employees accumulate tacit knowledge daily that sums up to intuitions about how change management is performing and how the change process is unfolding. Employees gather the insights that change management needs to move the process from poor change management to a tremendous change outcome. The figure below illustrates how harnessing employee predictions via collective intelligence technologies can be for a change process.
Projects that use collective intelligence technologies will either meet or succeed in objectives.
To illustrate how CI technologies can make the change effective and successful, let us use an example in an organization with many developed projects simultaneously. This scenario involves many people across different projects at the same time within the change process. The new-generation collective intelligence software allows managers to create a more efficient change environment and reduce their potential anxieties through monthly monitoring of all member intuitions during the change process.
Collective intelligence technologies enable project participants to contribute to collective work. In turn, they receive an overview of all the details of the company's project processes that are critical for them to make them feel that they are a part of the change and reduce their potential personal anxieties in the change process. The result is a boost of productivity by transferring some of the change managers' burdens onto the software.
Collective intelligence technologies can make communication between co-workers easier and faster, which means higher effectiveness and less bureaucracy for the organization. In other words, change processes become more democratic, benefitting both managers and employees.
For more information on Mindpool's collective intelligence technologies, please contact Søren Wiberg Holm on email@example.com.
Deloitte (2020). Combating COVID-19 with an agile change management approach A guide for organizations to prioritize people's needs while maintaining business continuity during uncertain times India perspective Retrieved from https://www2.deloitte.com/content/dam/Deloitte/in/Documents/human-capital/in-hc-consulting-deloitte-change-management-pov-on-covid-noexp.pdf
Hallin, C.A., Andersen, T.J., and Tveterås, S. (2017). Harnessing the Frontline Sensing of Capabilities for Decision Support. Decision Support Systems, Vol. 97, pp. 104–112.
McKinsey Company Inc., “Organizing for successful change management: McKinsey Global Survey,” 2006. Retrieved from: http://www.leadway.org/PDF/Organizing%20for%20successful%20change%20management.pdf.
Prosci (2018). Why change management. Retried from: https://www.prosci.com/resources/articles/why-change-management
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