GARY ALLEMANN We’re looking more at mines where there’s an economy of scale, and therefore making some investments in data makes sense
Covid-19 and the subsequent national lockdown have driven the demand for digital technologies, which has highlighted the importance of data management, governance and quality in the mining industry, notes digital solutions provider Master Data Management MD Gary Allemann.
“People working from home has created a data management burden on organisations. For example, with regard to security, employees are accessing secure data from their home or personal computers, through public Internet. There are ways of managing this, but it creates a burden on information technology (IT) systems, which was not there before.”
In addition to creating more visibility on how data is moved throughout organisations, Allemann highlights how this is also placing strain on public IT systems, with Internet speed slowing down, owing to more Internet traffic.
“This impacts on corporates. We want to minimise traffic and the data we send, ensuring that both are limited, thereby prioritising only what is necessary. We’re starting to look at demand management for our data, as well as access management. This involves data governance, and understanding who uses the data”.
Allemann particularly highlights the importance of digital technology and data in the context of the local mining sector which, similar to most other local industries, has been drastically affected by the economic effects of the lockdown.
“There’s an interest and need for skills and data literacy, as data is still a critical asset. Safety, operational effectiveness and supply chain management are three particular areas where data is a key resource in managing operations.”
The struggling state of the local economy is forcing mining companies to minimise spend on essential services, and Allemann notes an interest from mid-level staff in bolstering their own skills with data analytics and management.
Master Data Management offers certified training for information management professionals, which is also extended through global partnerships as electronically based learning.
This provides an in-depth understanding of data literacy, and exposes the local market to international best practice, experts, practical training and skills building, he explains.
He adds that the Covid-19 pandemic has emphasised the importance of online-based training, which has become more crucial, as it reduces the risks of infection.
One of the most important elements that data analytics and governance can help to streamline is keeping track of Covid-19 infections at a mine site.
Allemann states that this would help to prevent further infections and minimise disruptions, should an employee test positive.
“We need to become more accurate about understanding where our workforce is. It’s part of general safety reporting, but the pandemic will encourage this to include tracking where employees are on site, as well as where they are interacting with other employees, which could be used to assist in minimising infections.”
Additionally, this type of tracking and the data gained from it can be useful in the long term for general safety elements and reporting.
Allemann emphasises that data governance is often misunderstood as a discipline, and that it involves people in appropriate positions making important decisions about data, and how to use it.
This particularly becomes important with complex issues in the supply chain. This also often involves spending significant amounts of money to fix certain errors in the supply chain, such as migrating enterprise resource planning systems. This places more importance on decision-making regarding data.
Data governance can also assist in decision-making pertaining to purchases, particularly off-contract purchases.
“Data governance is about trying to identify how our data landscape supports our strategic buying decisions. It’s about deciding how to use data effectively – what data we need to capture, how to measure things and what needs to be measured.”
Allemann adds that data quality can contribute to its effectiveness – this becomes particularly important in instances such as keeping track of purchased materials, particularly materials that get captured in multiple and different formats.
For example, stock-keeping errors can occur when entries are being recorded manually, with the same transaction being logged twice. This can often cause errors with billing and payments, and addressing these issues will improve operational efficiency.
These errors can also occur when keeping track of employees, particularly migrant employees, with duplicate sets of data created when employees are on extended leave. Consequently, this makes the safety and tracking of employees more difficult, and has operational cost implications.
“There’s a lot of focus from experts on discussing business agility, and our ability to move in a new direction to make decisions quickly, and this is where analytics has a role to play. The ability to provide better information for executives and enable them to make the difficult decisions they need to make all revolve around data governance,” he concludes.