Understanding Key Indicators and Metrics for Management of Change

Worker Safety Helmet

How data visualization and analytics can facilitate decision-making and better MOC. 

Anyone who’s tried to drive change in a company knows how hard the process can be. 

People become stuck in their ways, dependent on the systems they use day to day. Rock the boat and disrupt their routines, and it’s fair to assume that not everything will go smoothly. 

While this is the way it is at organizations of all kinds, it’s especially the case for those in industries where changes can affect health, safety, or environmental risks. When regulatory authorities require that management of change (MOC) be included among your policies and procedures, it’s because they know that change can be difficult—and that getting change right can be critical. 

Here, we’ll take a look at what many now consider best practice when it comes to management of change: leveraging data visualization and analytics to optimize MOC-related decision making. 

The Importance of Data Visualization 

Thanks to ubiquitous digitalization, most companies now have access to data on every aspect of their operations. The consensus today is that “data is king;” and the more you can get, the better. 

But having access to data isn’t enough on its own. Organizations need a way to make sense of that data—to understand it and turn it into helpful information that can be used to make good decisions. 

Data visualization in the context of MOC involves taking a company’s data and processing it to create visuals like charts and graphs. With specialized software and powerful analytics tools, you can gather data from across your organization—on equipment, materials, systems, and the like—and present it in a visual format that’s easy to digest and interpret. 

The collecting process entails taking disparate data sets and bringing them together in a data lake. Once housed in a centralized repository, this cross-functional data becomes a single source of truth for the identification and analysis of organizational trends that may not have been obvious otherwise. 

Integrated Data Sets 

The key to effective data visualization for use in MOC is gathering data from across the organization. 

  • Safety and environmental data 
  • Engineering and operations data 
  • Quality data 
  • External data: customers, suppliers, sales and finances, HR, procurement 

For those at a company who are focused on management of change, data visualization can inform and accelerate the MOC decision-making process. When you know what you’re looking at and what the data say, you have what you need to manage risk and take action. 

Turning Data Into Insights for Management of Change

So what can you do when you have data at your fingertips and your job is to optimize MOC? If data visualization and analytics are in your toolbox, you can manage MOC tasks, measure MOC results, and use predictive analytics to ensure what you do today will help you succeed in MOC in the future. 

Managing and Management of Change

One of the biggest benefits of data visualization is how it can facilitate MOC task management. With an analytics tool at your disposal, you can plot, graph, and parse all MOC-related actions on a dedicated management dashboard. Among other things, such a solution can help you track: 

  • Open findings and actions for MOC 
  • Time to closure for MOC 
  • Pre-startup safety review (PSSR) start-up times and alerts and warnings 
  • Overall workflow movement and status 
  • Temporary-MOC expirations 
  • Emergency-MOC conversions to temporary or permanent status 
  • Risk assessment updates per MOC 
  • MOCs by reviewer or approver 

You can also track important MOC-related tasks like training programs, documentation updates, and the implementation of risk barriers and mitigations related to your ESG program. 

Measuring and Management of Change

Measuring in the management of change arena involves assessing the success your organization has had in meeting various MOC requirements. You can measure: 

  • Number of MOCs per site, and by type 
  • Number of risk assessments (RAs) impacted (and status of impacted RAs) 
  • Risk change as result of MOC (whether overall risk is going up or down) 
  • Number of MOCs in simultaneous operations 
  • Audits and assessments of areas where MOC has been implemented 
  • Number of MOCs impacting contractors or suppliers 
  • Number of MOCs requiring environmental review 
  • Number of MOCs that furthered ESG goals   

Measuring allows an organization to determine whether the changes it has implemented have been effective, and it provides it with a path forward—a baseline to build off for making changes down the road. 

Predicting and Management of Change

Finally, the prediction piece: using data from across your organization to anticipate and address MOC-related issues before they arise. With a predictive analytics tool, you can identify areas within your business where you’re likely to need MOC, for example, and you can calculate future risk based on current key indicators and metrics. Predicting involves analyzing factors like: 

  • Maintenance, procurement, and approvals history to determine where change (and MOC) may be needed in the future 
  • Number of barriers/secondary controls/backups utilized compared to incidents and near misses to identify potential problem spots and likely locations of future incidents 
  • Number of MOCs, open findings with high risk, lockout/tagouts (LOTOs), active safe work permits, etc., to calculate overall risk 

Predictive analytics solutions can even suggest corrective actions when they may be advisable. If the software identifies that the risk level in an area has gone from medium to high, for example, it may prompt the user to hold a safety meeting to do something about the elevated danger. 

Whether your MOC mission involves management and measurement, making predictions, or some combination of the three, better data visualization and analytics inevitably leads to better organizational understanding. It allows you to compare quality and safety data to anticipate and get ahead of potential challenges, and it can help you reduce and mitigate risks—and measure the impact of corrective measures already taken. 

Data visualization and analytics isn’t a panacea for MOC, but it can make the process easier and more effective. When you have the tools to turn data into insights for use in making MOC decisions, you can ensure that the actions you take will actually change your organization for the better.