Operational Technology in Local Government

An Enterprise Resource Planning (ERP) solution can be described as the ability to deliver an integrated suite of business applications with ERP tools sharing a common process and data model and covering broad and deep functional end-to-end processes, such as those found in finance, HR, distribution, manufacturing, service and the supply chain (Gartner).  

So what opportunities are we missing if that definition doesn’t incorporate the developing sprawl of real time Smart City focused solutions largely introduced by Sensor or Network Vendors.  

Acknowledging the immediate benefits of the solutions offered across the various asset sectors of Water, Energy, Smart Bins and the list flows, we can see that the underlying benefits that come with aligning situational real-time asset data as enterprise data, as championed by traditional IT strategies, will be lost if Councils silo vendors without a strategy to address the corporate value of the data as well as the opportunity to drive enterprise transformation in an  effort to lower costs, create efficiencies and enable continued strategic innovation.  

There is a growing number of examples where key data is lost to organisations when vendors of those niche solutions fail and collapse, or are small and don’t have the capacity to support integration requirements (and perhaps don’t have requirements to ensure data is available for the life cycle required by Council). Very often these growing number of solutions are providing immediate benefit but are not providing an enterprise or life cycle strategy using the data being collected. 

Understanding and implementing enterprise architectures consistent with the OSIsoft PI Platform can provide the solution. 

This solution provides an understanding of how a real-time data series system manages streams of IoT data and then contextualises that data into an Asset Hierarchy in order for it to be analysed and merged with other strategic organisational business structures to create transformation opportunities – such as changing assets from calendar based maintenance to condition based maintenance – or automating work orders based on condition based events – or ensuring notifications to both Customers and Customer Service Teams are automated based on fault or failures. 

One might suggest that understanding the need for a technology stack to manage Operational Technology would well fit with the Gartner position on a Pace Layered ERP strategyAs such it recognises a new and innovative model that has a different set of requirements outside those based on traditional transactional IT.  

Operational Technology can align to traditional IT stacks while building another part of the enterprise. Operational Technology is not a competing architecture – it is a complementary architecture. An architecture than can make sense of SCADA and other process systems, merge field IoT data or ingest data from data silos and then roll up all operational assets into the one data infrastructure platform. This simplifies the integration points, ingesting third party data for added value and provides the the one platform designed for big data and  predictive asset based analysis while working together with existing Asset Maintenance and Asset Strategy Systems.  

Stripping those specific operational opportunities, the same reason one might choose an ERP remains the same to aggregate real time data into a dedicated operational data management platform:

  • Improved visibility and access to corporate data 
  • Improved asset forecasting 
  • Organisational and Departmental Collaboration 
  • A scalable resource 
  • Cost Savings  
  • Integration of data with Asset Systems and Business Intelligence  
  • Business Transformation opportunities 
  • Enhanced Reporting capabilities 
  • Enterprise capabilities to integrate spatial systems 
  • A global architecture with roadmaps for on-going improvements 

However, choosing an OSIsoft PI platform also addresses the specific tenants that maybe overlooked if not experienced in choosing an Operational Platform:  

  • Data quality – The ability to ingest, cleanse, and validate data. 
  • Contextualized data – When dealing with asset and process models based on years of experience integrating, storing, and accessing industrial process data and its metadata, it’s important to be able to contextualize data easily. A key attribute is the ability to combine different data types and different data sources 
  • High-frequency/high-volume data – It’s also important to be able to manage high-frequency, high-volume data based on the process requirements, and expand and scale as needed. Increasingly, this includes edge and cloud capabilities. 
  • Real-time accessibility – Data must be accessible in real time 
  • Data compression 
  • Event Analysis – Enables a user to reproduce precisely what happened in operations process 
  • Statistical analytics – Built in analytics capabilities for statistical spreadsheet-like calculations to perform more complex regression analysis. 
  • Visualization – The ability to easily design and customize digital dashboards with situational awareness 
  • Connectability – Instruments, devices, networks and COTS interfaces 
  • Time stamp synchronization 
  • Partner eco-sphere  

As Councils move into the world of Smart Cities and look to create Smart Business Models, a key component will be delivering an enterprise strategy that is supported by an enterprise Operational Data Platform.

Operational Technology, such as OSIsoft PI, complements existing ERP architectures so that the goals of delivering greater community outcomes and developing efficient and agile organisations on the back of a platform that delivers real-time data infrastructure providing real time situational asset awareness and bridges existing IT architectures.

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