In mining and manufacturing sectors, where prices are often fixed or expected to fall, increasing profits is more than just increasing the selling price. Picking up the bottom line, operational efficiency requires improvement to lower production costs, increasing profit margins.
But, operations are often plagued with inefficiency due to poor quality data. The axiom ‘if you cannot measure it, you cannot manage it’ holds true. Meanwhile, data quality and master data management solutions ensure effective accurate information measurement to improve efficiency for profitable enterprises.
While data quality and master data management are tools often associated with the financial services sector, the fact is everyone needs to understand what is happening in their business.
The three main problem areas quality data assists in solving is mining and manufacturing operational efficiency improvement via asset management, supply chain and health and safety. These areas are plagued by unnecessary expenses and inefficiency driven due lacking quality data.
Realising maximum efficiency is vital to a complete view of the enterprise’s assets depending on their deployment. While most organisations have asset registers, inconsistencies creep in with object descriptions leading to problems, particularly in industries such as mining and manufacturing where distributed geographical locations have different data capturing methods.
For example, an asset could be described as ‘ACME Water Pump, 1500HP’ in the asset register, but once deployed is noted as a ‘Water Pump, ACME, 1500HP’, resulting in a double entry. Therefore, assets can go missing without anyone’s notice leading to unnecessary expenses when these objects need replacing.
Inconsistencies in the long-term means enterprises have no clear idea of asset lifespan or their location. Fault management becomes problematic since these may be logged multiple times, showing up as a different fault every time.
Data quality aids in solving these problems ensuring a standardisation of asset registers. A single version of the true assets, increasing operations.
Likewise, data quality improves supply chain management. Dealing with spend analysis, in terms of total spend per vendor and total spend on specific materials, equipment and assets, having an accurate view of your data is vital. It is impossible to gauge with your amount of money with inconsistent data across different geographies. This means supplier discounts are not accurately negotiated, because it is impossible to quantify spend. Determining if supplies are meeting their duration become ever more difficult too.
Restoring integrity and data provides a single, accurate view of spend. In turn, this provides information for making informed suppliers decisions, costing and the needs of various branches and their geography, aiding in improving efficiency.
Health and safety regulations assisted by quality data leads to efficient operations, and helps organisations in mitigate risk. State employees working underground in dangerous places need appropriate qualifications and health clearances. However, given the amount of contract work, particularly on the mines, employee data tends to duplicate across several HR systems. Re-entered each time an employee’s contract is renewed. Different locations under the same parent company may run different HR systems, making a centralised database difficult to manage. As a result, cost and safety compliance become difficult to manage. Up-to-date and corrected data ensures workers are qualified in the positions and medically cleared for them. Keeping track of records is impossible without data, increasing risk and liability if something goes wrong.
Ultimately, improving operational efficiency requires control. Without a unified version of data this control is nearly impossible. If the right information is available, using the right data quality and master data management tools however, this control becomes attainable. Optimising processes improves operational efficiency and ultimately boosts the all-important bottom line.
Gary Allemann, senior consultant at Master Data Management