Transforming mining operations and overcoming data challenges
AUTHOR
At Anaplan, we've had the privilege of working closely with numerous mining companies, witnessing firsthand the transformative power of Connected Planning for your industry.
Through our experiences, we've identified three critical ways in which data management practices impact the effectiveness of mining planning processes.
Traditional methods often fall short in meeting the evolving needs of the mining industry. In this post, we'll delve into the key challenges associated with data management for effective mining operations planning and highlight how adopting a Connected Planning platform can help your company overcome these obstacles.
Modeling and planning data
Old approach:
In the past, mining companies have relied on fragmented spreadsheets to manage their data. However, this approach is labor-intensive, error-prone, and lacks continuity across functions. For instance, compiling inputs from various sources becomes a cumbersome task, leading to delays and inaccuracies in planning processes.
New approach:
With Connected Planning, mining companies can leverage unified dynamic modeling capabilities. This approach offers flexibility, collaboration, and scalability, driven by finance and auto-aggregated data. By adopting this method, companies can streamline their planning processes, improving accuracy and efficiency.
For example, this will allow you to begin optimizing equipment pairing for maximum production capacity and revenue generation.
Analyzing data
Old approach:
Traditionally, data analysis in mining companies has been siloed, with each business unit and geographic location operating independently. This fragmentation often results in discrepancies in data sources and limited capabilities to adjust analyses as needed.
New approach:
Connected Planning facilitates auto-populated analysis from a single source of truth, enabling focused discussions on root causes and resolutions. By leveraging the most relevant and reliable data, mining companies can rapidly and accurately run analytics, enhancing decision-making processes. For example, you’d be able to assess the total economic value of an asset.
Decision-making using data
Old approach:
Isolated decision-making has been a common challenge in the mining industry, with a lack of visibility into underlying activities and business drivers. Additionally, there is often limited connectivity to other key systems of insight, hindering informed decision-making.
New approach:
Connected Planning enables linked dependencies, providing comprehensive insights into plan drivers and variance explanations. Mining companies can rapidly create scenarios with accuracy and collaborate on decisions, leading to more informed and agile decision-making processes.
For example, you’d be able to find the root cause of production gaps, create scenarios to compare potential disruption and impact toward the equipment arrival delays.
Workforce planning data
Old approach:
Long-range strategic planning and ongoing operations planning often occur in silos and disconnected spreadsheets across the value chain. This fragmented approach complicates decision-making and capacity management and can result in inefficient and costly hiring and shortage of skilled resources, which in turn has potential to negatively impact production capacity and maintenance scheduling, increasing costs and risks in health and safety.
New approach:
An integrated, connected approach to workforce planning enables organizations to better understand their labor demand and supply across a multitude of dimensions and to develop dynamic workforce plans in close collaboration across operations, finance, and HR teams. With a view into short- and long-term demand, including site production operations and plant maintenance, and the ability to account for different scenarios, teams can ensure workforce readiness in terms of capacity and skills to deliver on goals aligned with budgets.
Embracing a new approach with Connected Planning will enable your mining operation to continually model, plan, collaborate, adapt, and optimize financial performance and outcomes.
By addressing the challenges associated with data management, you can unlock new opportunities for growth and innovation in an ever-evolving industry landscape.