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Mac Consulting

Data Analytics for Community Development in the Mining Industry

Mac Minds Insights | Mac Consulting

It has been fascinating to see the changing approach of mining companies to community development and Corporate Social Investment over the past 20 years. The mining industry stands apart from many other industries in South Africa in that the community investment is regulated through the Mining Charter. Whilst initially this was merely a compliance exercise, there has been an evolution in thinking regarding the approach to community investment towards a more collaborative and data-driven decision process.

It could be argued that escalating social unrest – driven by the deterioration of the economy, municipal corruption and poor performance, as well as the demand for an immediate solution to the land issues in the country – has given rise to desperation to satisfy the demands of communities in order to maintain both a regulatory and social licence to operate. But we have also seen an honest desire by mining companies to gain the trust of their communities and stakeholders and see them thrive by undertaking meaningful community investment initiatives in a collaborative manner.

How does one define and deliver meaningful investment that makes a lasting difference to communities beyond the life of mine? Over the years, we have seen the Social and Labour Plan and the Local Economic Development space littered with a plethora of good intentioned yet failed projects that seem to follow the latest craze and end up defunct or barely functioning.

The mining industry has seen the value of data analytics in their operations and is now starting to question how these same disciplines can be used to model the impact and effectiveness of social investments. There is a view held by many that it is much easier to model the performance of a continuous miner over time in certain conditions than it is to understand the impact of the expansion project on the health and social cohesion of a mining community. But does that mean we should not do it?

This challenge was laid before our team. After consulting with close to 20 different roles and functions within a mining client which have an impact on the communities, it became clear that we needed to start at the very beginning of the data analytics chain by gaining a grip firstly on who was doing what, where, and with whom, before we could move to the more sophisticated process of predictive or, possibly, prescriptive analytics. With executive support, we moved to design an analogue geospatially referenced prototype in the social data analytics room in the executive suite. This helped the executives and the heads of the various functions to articulate what they wanted to analyse and visualise, and the ideas started flowing. The room became an exciting and energising place to visit. We then began translating these ideas into a digital pilot, leveraging existing technology, aligning with the longer-term data management strategy for the group and developing minimum viable product as a sandbox.

With the advent of COVID-19 and the realisation of the immense social and economic impact of the lockdown in the mining communities and on the country as a whole, buy-in and urgency increased, with customarily socially-minded community teams coming together to assist in the data collection, clean-up and visualisation of key community impacts and investments. This included collaborating with the CSIR and other government departments to obtain geospatially referenced data sets on COVID vulnerability, crime, and extrapolated community demographics data. This work continues as we see increasing economic and social vulnerability, as well as increasing crime in our communities.

The tool and the data analytics will assist the company in understanding investment opportunities, the risks, and the level of social license to operate so as to leave a lasting positive impact in the communities in which they operate. The journey is just beginning, but the foundations have been set to move to more sophisticated analytics for collaborative community development.

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