With decreasing ore grades, more complex orebodies and volatile commodity prices, the mining industry needs ways to work smarter and respond quickly to changing circumstances
The case for digital innovation in mining
Minimising uncertainty through the mining process, reducing costs and adapting to change are some of the drivers causing companies to look at digital innovation. Better performance and productivity are, of course, paramount outcomes.
There are a lot of areas where productivity and performance can be increased, and geoscience is one factor playing an influential role in defining productivity. Geoscience ensures we have the best knowledge of an orebody, and when that knowledge is transferred to those who need it, it is an extremely valuable resource.
In the past, mining and geoscience have been driven by long cycle time activities. For example, the time period between a sample being taken and mining was long and information management processes more manual.
Now as the industry searches for productivity and performance improvements, there is a need to better deal with variations – to accurately identify them and be able to react to these variations with efficacy. The ability to stream data and optimise processes to support the data getting in the right hands, at the right time, is critical. The cycle time for this process will tend toward transactional levels as the value for increasing process control and optimisation is realised.
What does it mean for geologists?
Many will identify with the sentiment. You’re a geologist and you just want to do your job: collect the data, discern the best data and make the best interpretations and decisions.
The crux of digital innovation is identifying how to transform current processes and embrace these new digital tools with confidence. There are two main things that need to happen: one is to understand how to consolidate the data from all these new devices, and the other is how to make it fit into the business.
There is a certain digital maturity lacking in current processes, which tend to be geared more toward long-term data usage. As a result, there is a tendency to massage data to get the data set together – then it is made available. With this kind of manual process, geologists will continually be challenged when needing to deal with more data sets, bigger data sets and more transactional types of data. To try to validate this, think of how much time is currently spent getting the data set together in an operation and how it is not scalable when there is a constant stream of data.
Making data fit into the business is the other challenge that needs to be addressed. Often there are many broken systems held together by band-aids, on which more band-aids are applied to support making changes. A full solution requires an upheaval that cuts across many groups and that is hard – if not impossible – due to strong functional cultures that exist.
An example is the seemingly simple action of naming a drillhole. A classic scenario is that there may be a geologist, a driller and a surveyor all standing at a rig with different versions of the same data. It takes ‘old world’ verbal communication to hang that data together.
For digital innovation to thrive, the ability to source trusted data without the reliance on manual processes or specific personnel is fundamental. Hence, the transformation toward being able to deal with streaming data, and deep process optimisation to support that data to get in the right hands at the right time, should be considered somewhat critical.
Creating the environment
Companies must be amenable to creating the environment in which digital innovation can thrive. First of all, there is the need for ready access to data. All the data must be there and available when and where staff need it. It must be available for any level of decision-making – without having to go to a technology expert each time.
Secondly, trust in data quality must be forged. Of course, this may take some time, but it is essential. Geoscientific data is an extremely valuable resource. An organisation’s commitment to building a cohesive data source will, over time, build consistently good experiences with the data and, in turn, build trust.
Consolidated management of data
Currently, there are multiple data sources and multiple users who all need the data for different purposes. The obvious consequences are that there is greater risk of inconsistent translation of data and erosion of trust – not to mention it is time consuming and repetitive.
A typical advancement on this is the consolidated management of data from different sources, so that the data becomes available via a one-stop shop. It facilitates increased trust in data as data quality is checked, assured and cross-referenced. Consolidation also brings consistency to data and effective delivery. Ultimately, all these elements lead to a consistent, positive experience with the data system that forges trust and increased usage.
In order for the successful consolidation of data to occur, the way in which data is transferred must be reviewed. Currently, the data from different systems is delivered to an endpoint and it is the responsibility of the user to complete the connection. Whilst this process may provide great flexibility, it raises the problem of diminishing value of data.
As most currently used endpoints are generic, a diminishing of the value of data occurs through each exchange. This is because the data does not map properly with generic endpoints. As a result, the value of the data is a fraction of its original worth.
The ideal future state is that the transfer of data is a fully facilitated process where there is true connectivity via a managed business-system to business-system transfer of data that is based on accepted standards and protocols.
Connectivity is facilitated by a solution developed end-to-end through collaboration between vendors. This ensures good data management takes into account the process that happens in each system, and the solution is updated with changes in the systems. It allows for the incorporation of the vendors’ expertise into the entire solution, rather than just their part of the problem. Connectivity also ensures the implementation of good data governance that provides secure data transfer with a low risk of data manipulation.
The leverage point for innovation will be the transformation of current processes to enable miners to deal with new digital tools and technologies, and it cannot be achieved by simply slotting in new technologies to facilitate the same old processes. Many companies work on a broken and incohesive system of data collection. What is really needed is supported change. The full solution requires an upheaval that cuts across many groups and, indeed, the many strong functional cultures that exist.
Of course, this type of cultural transformation will be challenging. The path to being able to do this is not quick and groundwork is needed. The upside: a transformation to stream accurate, consistent data and deep process optimisation to get that data in the right hands, faster. Cross-functional, total-systems thinking will be the champion for digital innovation in mining.