I am often asked: ‘How can resources companies drive greater productivity and efficiencies when capital is constrained, human resources are scarce, and innovation is perceived risky?’
Taking a Software as a Service (SaaS) or Platform as a Service (PaaS) approach is fast becoming a preferred strategy for mining firms looking to optimise operations across the enterprise, without needing to invest in physical infrastructure or additional staffing resources.
Working in the spatial technology sector, I’ve seen first-hand the considerable productivity and efficiency gains a managed GIS service can deliver; and have worked with a number of leading companies recently to establish a Cloud GIS solution for this reason.
An example that stands out is St Barbara – an innovative gold mining company with assets in Leonora, Western Australia and Simberi, Papua New Guinea.
Like many resources firms, St Barbara had a well-established GIS solution in the past, however this had become out of date during the mining downturn. They approached us to modernise their GIS platform to establish an enterprise-wide solution that could optimise productivity and boost efficiencies across their operations.
There were a number of challenges to deal with, including:
- Users at regional mine sites experienced poor system performance and data access as a result of limited bandwidth and outdated data access methodologies. They wanted to improve service and accessibility for all users and to ensure the platform was scalable and robust enough to meet business requirements over the next 5 years.
- They currently outsourced their IT management and had minimal internal spatial resourcing to manage an enterprise GIS environment.
- They were keen to streamline their data management practices and utilise location data direct from 3rd party data providers. In other words, they wanted to avoid downloading large datasets that required local version control – and instead rely on dynamic feeds, direct from the source.
After assessing a number of options, St Barbara opted for an Esri Australia managed Cloud Services offering, which gave them access to the full capabilities of the ArcGIS platform without the need to invest in physical infrastructure.
Outsourcing the hosting of their GIS also removed the need for St Barbara to manage and maintain their ArcGIS Enterprise environment – enabling their IT team and partners to remain focussed on their core duties.
Our Professional Services and Cloud Services team worked closely with St Barbara to ensure the solution would meet the evolving needs of the business. This included migrating data and projects to ArcGIS Pro (from ArcMap), providing project management and site configuration services, and delivering training services and support to key St Barbara users to ensure they could continue to build and develop in-house capabilities.
The business benefit to St Barbara of taking a managed services approach has been extensive, but there are four areas in particular I would like to highlight.
- As said earlier – it frees up their highly skilled internal staff to focus on their primary business function of providing St Barbara with accurate, useable and up-to-date data.
- It also provides an improved mechanism for the dissemination of this data across the entire organisation – removing significant duplication of effort and numerous work arounds.
- The platform has the capability to automatically scale to meet demand and capacity, if required. This ensures the solution will continue to support St Barbara well into the future, as adoption grows, but in the short-term they are only paying for what they need.
- Finally, as a result of the system modernisation, all users across St Barbara now receive the same high performance and easy access to data – regardless of whether they’re working in head office or a regional site.
With a robust and modern Cloud GIS solution in place, St Barbara is now well-positioned to deliver new capabilities such as field mobility, dashboarding and self-service GIS.
About the author
Business Development Manager