The Connected Workforce: Comprehensive Digital Workforce Strategies for Operations Management

In order to retain competitive advantage, the industry is adopting digital solutions in a rapid pace. Processes and tools that are inefficient and paper based are transformed to digital counterparts that enable organizations to drive continuous performance improvements. Benefits of digitalization include reduced incidents and accidents, less asset downtime, improved efficiency and a reduction of costs related to audits and compliance.
To keep operations safe and intelligently map out risks, solutions are being adopted at scale for assessing risks, determining personnel competence, managing safety instrumentation and alarms, issuing work permits, and so on. These solutions all fall under the umbrella of automated Operational Risk Management (ORM).
For effective ORM, solutions need to be capable of getting data to where it is needed. Operational data is typically scattered across multiple systems and locations. Asset registers, procedures, real-time data, alarm and trip settings, safety studies and so on. But more problematically, all these sources use there own terminology and support the methods from their own domain. For example a barrier, in the domain of PHA's it is called a safeguard, in LOPA we call them IPL's and in Enterprise Risk Management we call them controls. And not only the naming convention is different, also the criteria differ.

Let’s look at an example of a PSV mounted on a separator. It’s purpose is preventing that an overpressure will lead to the failure of the containment.

• In the PHA overpressure is listed as Cause and the 2 redundant PSVs as Safeguards
• In the BowTie overpressure is a Threat and the the PSVs are Barrier Elements
• In the LOPA overpressure is related to the Initiating Event and the PSVs are an IPL
• In the maintenance management system (MMS) the PSV is labelled as safety critical and assigned the SCE Group "mechanical relief"

Although there are tools on the market (such as Viewport.ai) that integrate and map data from various sources and can work with poor quality data, for any successful and sustainable implementation of such an integrated Risk Management approach aligning the concepts and domains is also necessary.

Presenter has, based on 25 years of experience within various industries, developed a comprehensive Risk Taxonomy. This Risk Taxonomy visualizes how terminology from various domains and methods relate to each other and what the differences are. It explains how, starting from the risk, the different domains like PSM, EHS, Security Risks and Enterprise Risk Management can be integrated. Allowing for slicing and dicing of information to support risk management at various levels in the organization, from C-Suite to work floor, and in various departments.

Taking the PSV of the example above, a single piece of information that there is preventative maintenance (PM) overdue can now be aggregated and viewed from different angles, e.g.:

• Operational view – barriers are degraded in a location where I want to do an activity (e.g. Hot Work)
• Technical Authority/Engineering view – as part of the mechanical relief programme
• Process Safety view – overpressure scenario not sufficiently managed, increasing the likelihood of a loss of containment
• Asset Integrity Management View – as indicator for how the maintenance management process functions
• EHS view – compliance to the maintenance procedure, as part of the management system (based on e.g. ISO9001 or ISO14001)
• Enterprise Risk View – indicating less effective management of major hazards/risks, included in the corporate risk register

Implementing an integrated risk taxonomy is not only foundational in realising integrated risk management. It also supports additional learning loops where all information is taking into account e.g. when updating our periodic safety studies and risk assessments.

Take Separator from the example, making sure that we have the following information from the last 5 years available when doing our PHA:

• MOCs applied
• Challenges to safeguards
• Overrides and inhibits that were placed
• Operating window deviations that occurred
• Cross check of safeguards vs. critical equipment in the MMS
• Relevant Incidents
• Backlog maintenance reports / overview
• etc.

And validate our assumptions on likelihood of the scenario’s, credits taken for the safeguards / IPLs, level of compliance of maintenance, rigor in the management of safety critical devices, etc. Leading to improvement of our studies and align the outcome with the actual risks in the organization instead of a “theoretical” based on industry data.