Home > Uncategorized > Mine Value Chain Analysis – part 1

Mine Value Chain Analysis – part 1

The worlds mining operations were hit hard in 2009 when the prices of commodities drops significantly and many halted production, cut work force, and sell unproductive assets. Year 2010 shows a better commodity price upward run and many companies are pursuing new investment opportunities. Some companies pursue organic growth while others identify mergers or acquisitions. Whatever the longer term strategy chosen by companies, a recent article by Glenn Ives in Mining.com magazines provides some points for executives to focus on as top issues in their mining sectors. By looking at those issues executives can avoid scrambling for solutions without effective strategic guidance when things unfolds differently from the current strategic plan assumptions.

While strategic planning process provides general guidance for companies ability manage their performance, a more tactical approach must be employed to enable finding opportunities that would allow better executions of those strategies through the mine operations value chains. The key words during these days of constrained capital access is PRODUCTIVITY. In virtually all mining industry segments and across all geographical boundaries, multifactor productivity (MFP) lags manufacturing and the economy overall productivity trends. Business process improvement program is one vehicle that may be used to improve productivity in the mine. Many companies set up enterprise driven effort for enterprise business improvement using Six Sigma or other methodologies that focuses on asset performance management. I believe managing asset performance is as important as identifying the performance of assets as parts of the overall mine operations value chains. Focusing on an asset performance without considering the effect of upstream and downstream processes on that asset will not be effective so we need to be able to see the performance of current processes and identify opportunities before deciding to implement business improvement initiatives that are costly and has isolated benefits with positive or negative affect on other processes within the mine value chain.

In many mining companies, significant efforts have been performed by multiple parties within to improve their business covering people, process, and technology. To start identifying productivity improvement, an overall view of processes involved in producing revenue to the company (converting ore to valuable commodity products) is needed to give visibility to the key revenue drivers. There is also a need for transparency to the key revenue drivers will promote awareness for companies’ stake holders to better focus
on the right Key Performance Indicator (KPI) for future business improvement initiatives. One methodology to consider is mine value chain analysis which is a simple methodology to map the current business processes, review and measure the performance of major processes in the mine value chain, and identify opportunities for business improvements. What are we trying to achieve with this methodology is

  • 1. To map the mine core operation business that provides economic value for the company from mine supply chain perspective.
  • 2. To identify value chain of the processes, systems, and significant drivers that provides the most benefit to the company.
  • 3. To provide transparency to the overall cost and revenue drivers of a mine operation by providing process driven data which is reliable and timely, so the company stake holders can focus better on the right KPI.
  • 4. To develop a model that represents and correlates discreet mine’s process matrix against productivity
  • The biggest challenge when doing this exercise is the mine value chain analysis team knowledge of the mining operations processes from planning, drilling and blasting, excavation and hauling, ore processing, all the way to product transport and shipping to the marketing planning for the products.  Another important challenge is  accessing the operations data for analysis, NOT necessarily the availability of the information but more  to isolation of valuable data which may requires the team knowledge of not only data integration and computer skills but also advance statistical analysis knowledge to separate highly correlated data based on knowledge of mining processes as well as statistical output.

    To be continued…..

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