Indirect materials make up a large portion of the working capital in mining companies. However unlike manufacturing, indirect materials in the mining industry heavily impacts on the people and therefore significant savings are achieved from both inventory optimisation and improved process efficiency once these materials are well managed.
Quality data with analytic reporting offers mining companies the ability to unlock costly overstocking and improve productivity across the supply chain. This in turn reduces costs and delivers clear ROI to management from indirect materials management.
Data Governance Delivers A Competitive Edge
Traditionally mining companies would outsource the cleaning of their data only to return it to old habits for it to slowly erode until the next clean up. With solutions now available to manage data quality internally, the overwhelming benefits of positive long-lasting change and savings cannot be ignored. Behind all good data lies data governance, a structure that enables the continual improvement of data when both active and passive governance is applied across the business landscape.
MDO MDM (Master Data Management) combined with MDO DIW (Data Intelligence Workbench) provide a powerful solution to build and maintain data quality including reports to drill into every aspect of business data to deliver savings.
At the highest level, ROI is achieved through indirect materials from:
1. Intelligently creating and maintaining data in a simple and effective manner that adds value to the business (MDO MDM)
2. Reviewing the quality of business data to target areas of improvement (MDO DIW)
3. Business Process Improvements through a proactive approach to data and process automation (MDO MDM, MDO DIW)
Through the implementation of MDO MDM and MDO DIW, ROI can initially be achieved in the following 3 key areas:
1. Productivity – reducing the amount of reactive work frees up an employees’ time to be proactive. A good example of this is using MDO to create multiple sets of master data within a single request. Some examples are, material creation, Purchasing Information Record creation, Source List creation, and BOM (Bill of Material inclusion) all within a single material creation request. This enables process automation from day one.
2. Setting KPIs and Metrics – by driving the work force to a proactive environment companies can then focus on delivering results:
a) Purchase Order Automation should be greater than 80%. The greater the focus on data quality, the higher a company’s ability to automate processes which reduces the cost of purchase order creation through speed and time.
b) Free-Text POs should be less than 10%. Data governance combined with data analytics enables companies to see the percentage of Free Text spend and then start reducing it. This results in increased stock turns and improves the use of working capital.
3. Stock Turns. Stock Turn data shows the health of inventory and is directly impacted by the amount of free text spend. While SAP captures stock turn data, integrating it with MDO provides a key indicator to deliver ROI through data analytics of supply chain lead times and governance of reorder points.
Using MDO DIW and drilling further into data quality, companies can uncover further levels of savings. Below are some examples:
1. Ensuring all Critical Materials are on contract. This reduces risk to the business and greater equipment availability.
2. Critical Materials should never be out of stock. By running stock out reports on critical materials companies can further define materials and ensure they are carrying the right amount of inventory.
3. All Stocked Materials must be listed in a Bill of Materials (BOM). When materials are catalogued and listed in a BOM there is a reduced need for free-text spend to occur resulting in better use of working capital (increased stock turns).
4. All Stocked Materials must have at least one Info Record (PIR) created. Info Records are effectively the Purchasing Master Data for materials specific to a vendor, when this data is maintained a very important link in the supply chain is achieved that lead to PO automation and reduced noise in the business.
5. Average Lead Time reduction. Lead Time is a key input to calculating stock levels so every reduction in the Average Demonstrated Lead Time can be calculated into a working capital savings. A handy metric for all Category Management Teams.
6. Value of Surplus Inventory. Any stock on hand that is above and beyond the planned maximum stock holding is Surplus to requirements. The volume and value of this inventory needs to be monitored. How surplus stock is created needs to be understood so that actions can be taken to reduce and eliminate this waste.
7. Value of SLOB Inventory (Slow and Obsolete). In all MRO stock there will be a portion of this stock that is potentially obsolete, having visibility of this inventory is required so that it does not get out of hand. This can be achieved with regular reviews by the business.
All new materials are proactively generated in accordance with the established governance standards. Included are intelligent rules and dependencies that simplify the process.
Using data analytics to run data quality checks as part of an end-of-day process to improve and maintain the integrity of your data.