The three essential steps to successfully integrating GIS in asset management

Having incorrect or outdated information can cost a utility or infrastructure-orientated organisation dearly in terms of lost time, wasted resources, damage to property, injury or worse. Imagine if your Dial-Before-You-Dig report was incorrect before you broke ground!

Managers and Engineers rely on having access to the most current information to co-ordinate teams and allocate machinery or other resources to time-critical jobs. Bottlenecks or delays in real-time information transfer between key corporate systems can result in different systems reporting different information about the same incident. This happens all too frequently when data is required across multiple systems and snapshot copies of data are transferred periodically between systems. The result is that the systems are almost always out of sync and the lack of up-to-date information can result in a small, preventable issue rapidly escalating to become a big problem.

Breaking down data silos

Historically, deciphering the location of an asset or maintenance event in an Asset Management System felt a little like trying to solve a Story Sum for a Maths exam at school. You remember the kind of thing: “the faulty valve MWVALVE1234 is located on the kerb outside 13 High Street which connects to water main WMAIN7654 that runs down the south side of High Street…”.

In the mid-1990’s Geographic Information Systems (GIS) reduced this complexity by allowing assets and maintenance requests to be mapped and overlaid with an unlimited number of complimentary mapping layers such as street names, property boundaries and aerial photography. This meant that maintenance event and asset data could be recorded and managed within the Asset Management System, while location information could be managed exclusively within the GIS. Maintenance crews were finally able to plan routes between jobs that reduced travel times and improved service response times.

As information technologies and enterprise asset management systems (EAMS) continued to evolve, many enterprises found themselves with a wealth of descriptive information about assets - costs, location, performance - residing in different systems and, sometimes, that data was in conflict. The extent to which this information remains locked in the silos of disparate information systems, rather than accurately and reliably available when and where it's needed, relies on effective integration.

Enterprise asset management as a concept is really the ability to access and use the right pieces of information (and that information needs to be descriptively and temporally accurate and authoritative) from enterprise IT systems. Organisations that have mastered asset information integration often see GIS emerge as a critical central point of entry to information from other corporate systems - financial data from the ERP, As-Built drawings from the corporate document system, or monitoring data from SCADA - accessed by clicking on a map.

How to integrate asset information

It has been COSOL's experience that enterprise asset management is only achievable when multiple systems are properly integrated, creating an asset information ecosystem. In this way, data is collected, stored and maintained in the application best suited to individual enterprise asset management functions across the asset lifecycle. An integrated information ecosystem accesses the best data from each system to present a collective and actionable description of an asset, how it affects others related things (customers, service levels, other assets in the network), its condition, maintenance history, cost to build, cost to maintain, and so forth.

However, there is rarely a plug and play solution to connecting corporate systems without introducing a whole new set of challenges - such as incomplete or inaccurate data, slow system performance or duplicated data sets.  Here's our three-step approach to delivering robust asset information integration:

1. Mapping the asset information ecosystem: understanding your data and systems

Some combination of ERP, EAMS, document management, and GIS software applications is likely to be found in most asset-intensive operations. The key to a successful asset information ecosystem is having clear processes and ownership rules for the data flowing between them. A task complicated by the fact that individual data points, and the applications in which they are maintained, may change over the course of the asset lifecycle.

Designing asset information integration therefore goes beyond identifying the various software packages in play and finding the APIs that connect them. COSOL has helped clients unravel the "spaghetti soup" architecture that results from this approach, where huge numbers of interfaces add to support overheads and limit the ability to apply new software upgrades. Rather, mapping the data attributes you need to collect to support business processes and the applications best suited to managing that data across the asset lifecycle is the best place to start. It may seem to be a matter of simply storing the mapped object (a point, a line or a polygon) and its unique Asset Identifier in the GIS and everything else relating to the asset (including its GIS identifier) in the EAMS. In reality, this seldom works. For example, a linear asset has length and a polygon has an area and these are best stored within the GIS so that edits can easily be tracked. Considering that there is a lot of attribute data, documents and media associated with assets, along with comprehensive maintenance and inspection history, careful planning is required to ensure that the replication of data between systems is seamless and meets business objectives. 

2. Preparing the site: integration planning to good practice principles

Before building connections the business rules for integration need to be established, and there are a number of best practice principles that can be applied. Which data is required in real-time versus updates that can be processed outside peak operating hours? How often is a full sync required versus only the data points that have changed since the last update? Defining a Common Data Model provides a single, shared language for the way assets will be classified, named, related to each other and the attributes to be recorded across the full range of asset management processes and systems.

Like the preparation that goes into painting your home: the time you spend scrubbing with sugar soap and masking up the window frames may feel like it's just delaying you from getting on with the rewarding part of seeing your new colour scheme come to life, but the effort will be worth it in the end.

3. Executing the Change: Technical approaches to Maximo/Esri Integration

With the preparation complete comes the final step of building the connections between systems and there may be a variety of methods for achieving this according to the applications you're using. Some software vendors may offer 'embedded' integration capabilities that are little more than import/export functions. This manual process requires human intervention and is fraught with potential glitches during processing. Other options include presentation level integration, where data points from various sources are passed through a user interface such as a web-page URL; workflow driven processes, where actions in one system are triggered by an event in another system; or full communications-level integrations using third-party middleware to facilitate data transformation.

Integrating GIS data across the asset information ecosystem introduces a new level of complexity and care should be taken to align each of these three steps with the desired business outcome. We'll explore each of these steps in further detail in future posts.