Digital transformation consists of multiple interdependent and intersecting changes driven by technological disruption. An organization’s ability to not only survive digital transformation but thrive, is dependent on its ability to manage complex change with a cohesive strategy. Research data from multiple sources indicates that slightly more than half of major change initiatives are viewed as successful. That means that nearly half fail to achieve their goal, a clear indication that organizations will need to sharpen their change management skills to transform to the digital state. Does your organization have a plan in place for managing digital transformation?
“Lead, Follow or Get Out of the Way”
When it comes to the unstoppable force that is the Industrial Internet of Things (IIoT), this is sage advice from US General George Patton as these are the three choices available to organizations. Leaders will thrive, followers will survive, and those that choose to get out of the way do so at their own peril. The leaders will be those that excel at implementing disruptive technology and leveraging the data it provides to strategic advantage. A few years from now, when we study this initial wave of IIoT adoption, this analyst expects that the leaders will have also excelled in managing change.
Strange perhaps to discuss management of change (MOC) at a technology conference, but ARC did just that last week at its 22nd Annual Industry Forum in its “Digitization of Asset Performance Management” workshop. As the initial IIoT killer app, asset performance management will transform the who, what, when where and how of maintenance and operations. According to workshop moderator and ARC Sr. Analyst Paula Hollywood, “All the technology in the world will not successfully and sustainably transform an organization without including the people who perform the work and the work processes they employ.” Check out a blog written by my colleague, Greg Gorbach.
Management of Change Basics (MOC)
What’s the big deal? Change is all around us. It seems simple enough, so why aren’t all major change initiatives successful? Obviously, the process failed somewhere along the line. Perhaps it was in building the business case; drivers were not accurately identified or weaknesses and threats understated. Did an unanticipated change in regulations have an impact? A leading cause of failure is the inability to clearly communicate change to internal and external stakeholders. Timely communication to employees, partners, and customers is critical to obtaining their acceptance and collaboration. Technology can be the easy part. Getting people to change can more challenging, making workforce engagement a critical factor to success. Was the workforce not fully engaged in the process? They must implement the tactical aspects of technological disruption and deserving of a seat at the MOC table as their feedback is essential to sustaining change. Managers must identify the workforce leaders who will guide their peers and hopefully bring any resistors on board. Most importantly, failure to properly train the workforce in the use of devices, software, and work procedure jeopardizes success. Biting off more than can be chewed, so to speak, is another leading factor to change failure. Pilot and scale is a familiar term to IIoT implementers, meaning test on small scale, prove success, and grow it in size. For APM purposes, user case studies indicate this approach to be successful. However, this phased roll out approach becomes much more complex in large-scale deployment of new business models. Regardless of pilot size, the intended strategic objective(s) must be the impetus of the endeavor.
The consequences of failed MOC are enormous! Unlike previous industrial revolutions where machines displaced human work, the IIoT revolution replaces brain power with artificial intelligence. The challenge for digital transformers is merging humans and AI. The very nature of AI can create distrust between humans and the data generated artificially. That could be a demotivator for the workforce and potentially negatively impact productivity. It could also lead to increased turnover as unhappy workers seek to change their environment. Resources dedicated to the effort are essentially wasted due to the inability to leverage or scale. Ultimately, all these factors crush the bottom line.
Keys to Success for Managing Digital Transformation
In successful MOC, the most important responsibility for executives is to walk the walk, and talk the talk. They need to demonstrate the behavior they desire to implement. They must communicate the change loudly, broadly, and clearly throughout the organization with defined goals that set the vision for the organization’s desired state with a sense of urgency. They must establish a cross functional team representative of all constituents in the organization impacted by the change. The feedback from this team will have tremendous impact on change tactics. This team along with management should define the change milestones with KPIs that are both measurable and achievable. Last, but not least, celebrate the wins to instill a sense of achievement and nip resistance in the bud.
This is the first in a series of blogs dedicated to the Digitization of Asset Performance Management and MOC. Check back soon for more.
About ARC Advisory Group (www.arcweb.com): Founded in 1986, ARC Advisory Group is a Boston based leading technology research and advisory firm for industry and infrastructure.
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About the Author:
Paula’s focus area is Asset Lifecycle Management and Asset Performance Management, specifically Plant Asset Management and Asset Reliability. She also contributes to ARC’s Process Automation and Field System teams.
Paula’s focus is on Asset Lifecycle Management, specifically Plant Asset Management and Asset Reliability. She has authored Worldwide Outlook reports in both of these areas of the Asset Lifecycle Management domain. Other areas in which Paula has been involved include Field Devices (Flow, Level, and Pressure), Process Analytical Chemistry, Intelligent Pumping Systems, and Laboratory Information Management Systems.