The Role of Data Quality in Fighting Financial Leakage
Financial leakage can affect any organisation, making it vital to review workflows and processes regularly.
Improvements can take various forms, ranging from conducting training sessions, implementing consistent processes, to integrating more effective technology. However, a major contributor to financial losses often goes unnoticed during audits: inaccurate data.
This article primarily focuses on drilling and sampling workflows within the resource industry. It explores their creation, the influencing factors like personnel, equipment, contracts, and data collection, and activities that can result in financial losses.
We also offer recommendations for businesses to enhance their workflows across these factors. Additionally, we delve into the significance of accurate, real-time data in boosting efficiency, enabling informed business decisions, and ultimately improving operational profits.
Reducing waste boosts efficiency
Often stemming from a lack of process and quality control, inaccurate data leads to business decisions being made on the basis of poor or incomplete information. This further results in the inefficient application of funds, billing errors, or improperly allocated resources – in other words, financial leakage. This is a common issue across all sectors, and the mining and resources industries are far from immune.
While inefficiencies occur at all stages of exploration and mining, our focus here is on drilling and sampling workflows, which are relevant across the industry from grassroots explorers to established producers. Accurate, real-time data can greatly enhance efficiencies, enable informed business decisions and improve operational profits.
Workflows and processes: design is key
Rather than being based on best practice, workflows and processes are often shaped by the ways in which personnel worked at previous sites. When these processes do evolve, they do so in reactive patterns or in response to the arrival of new team members. Ideally, workflows would be defined based on creating an efficient process. Any changes to the workflow would require change analysis (including risk) and include quality control milestones.
A generalised workflow showing investment versus risk is shown in the image below. The cost of inefficiencies in each of these areas is directly inverse to the amount they cost to maintain, meaning that data inefficiencies – the lowest cost activity – are potentially the biggest risk item.
Leakage risks in drilling and sampling workflows
The specific potential financial leakage risks in drilling and sampling workflows are many and diverse in nature. Common risks include:
- People are making decisions on a daily basis which affects the project and its operational success.
- They may be inexperienced, or not focused on maintaining knowledge of best practice.
- They are often given a task without proper handover or training and try to ‘wing it’.
- Plant operation is not something commonly taught at university or in vocational training courses.
- Personnel need training to understand the application of each type of plant, from bobcats to bulldozers to lighting plants.
- Personnel need to understand the hourly cost of plant and the implications of common errors, including using the ‘wrong tool for the job’, not being ready for the plant when it arrives on-site, or keeping the plant ‘on-hire’, or when it is no longer required.
- This is a vital area where operations can reduce leakage.
- Drilling and laboratory contracts are administrative tasks. As such, many operational personnel believe it is the role of administration or accounts to monitor.
- Often contract performance, if reviewed at all, is at the end of a campaign making it difficult to implement any corrective actions.
- Results often come back from the lab and it is identified that a hole was pulled up in mineralisation or conversely goes many meters past the target zone.
- Personnel may not understand the cost of consumables, downtime/demobilisation, meterage rates or the impact of other decisions on the cost of a drill hole/campaign.
- Drill plods are signed off with incorrect activities, consumables or meterage resulting in the contractor being overpaid.
- Time-consuming and ineffective logging methods (such as paper instead of digital recording) are common.
- Entering data captured on paper is time-intensive.
- Codes may be interpreted and entered incorrectly when translated to database library codes.
- The delay between field logging and data logging can be many days, preventing business decisions from being made in a timely manner.
- There are many methods available to determine mineralisation, mineralogy and a host of other factors, but determining the most effective method will depend on factors such as type of mineralisation; stage of exploration or mining; experience of personnel; budget and location.
- Sampling workflows must include quality control.
- Errors resulting in incorrect or lost data are common. Samples must then be retaken.
- Errors can be attributed to:
- sample number allocation
- not including QC samples
- providing hard copy or PDF sample numbers to labs
- providing inconsistent sample dispatches to labs
- not using appropriate standards.
Seeking solutions for leakage
The lists above are not exhaustive, and any of the issues mentioned can result in costly errors, inefficiencies or decisions made on outdated or inaccurate data. The upside is that there are solutions that can be implemented immediately, making quality data available for accurate, real-time decision-making. In order to do this, it is recommended workflows and processes be reviewed as follows:
- Contracts should be regularly reviewed to ensure they are fit for purpose.
- Drill plods should be reconciled daily (not at the end of the program) to check performance using real-time data.
- Lab and drill rig performance should be reviewed against contractor KPIs to make any changes.
- Monitoring the contracts in real-time – a process that includes checking PLODs and lab invoices are accurate – will reduce errors.
- Plant tracking should be in place to keep track of all plant on-site and ensure it is off-hired when no longer needed. It should be clear who is responsible for tracking.
- Ensure the person responsible is trained in the application of each type of plant and cost implications.
- Field data should be captured digitally and in a consistent format. This includes all data: geological logging, survey data, pXRF data, mag sus, hyperspectral, drill plods and so on.
- Data should be synchronised to the corporate database for immediate availability.
- Digital sample submission should be used as it allows labs to receive and enter samples into their systems quickly, with a greatly reduced risk of error.
- Digital sample numbering should prompt users to include QC samples to improve data quality.
- Regular review and analysis of sample QC data received from the lab will enable rapid identification of issues in lab performance and effectiveness of standards.
Roles and responsibility help to close the gaps
While every member of an organisation is responsible for improving efficiency, having a ‘champion’ helps to define, communicate and provide training on efficient processes. All personnel, regardless of experience, then have processes to guide them in their activities. Strong and consistently reinforced processes will positively impact all aspects of operation, from planning through to lab analysis and data interpretation.
It is important to provide access to data for all stakeholders, from management and geologists to field workers. This avoids data loss, multiple copies of data and delayed decisions. Different access levels can be defined by data management applications, enabling real-time access for data review and analysis, QAQC interpretation, spatial plotting, reporting and download without compromising integrity.
Solutions for Digital Data Efficiency
There are many ways to reduce inefficiency, but all are worth exploring. Implementing just a few of the recommendations detailed above will result in improved quality and availability of data, ultimately enabling better-informed business decisions and reduced operating costs.
maxgeo’s software and cloud-based solutions are a proven way to reduce leakage and improve the quality of data available for strategic decision-making.