CSR Analytics: Quantifying the Human Dynamics of CSR

A few weeks back we had this question put up on our student forum, “Do you see organizations leveraging CSR Analytics as an easy-to-use tool to improve employee engagement and employee self-worth? Describe some instances that you find relevant and educative for the audience.”

I think this is a very interesting and relevant question and thought to share the response I gave on the forum with all of you as well. Do feel free to get back to us with your thoughts.

In India, spending on Corporate Social Responsibility projects is now mandatory for business entities that meet certain criteria of size and revenue1. Estimates on future spends on CSR in India ranges from INR 8700 Crores3 to INR 20,000 Crores2 (approx. USD 1.4 to 3.2 Billion as of Nov. 2014 exchange rates), by a total of about 6000 companies2. As such, the new mandatory CSR regime will unleash a new CSR “market” in the Indian socio-economic sphere:

With any such emerging and high-velocity market comes new sets of challenges and opportunities.

Challenges arising from mandatory CSR

India is the first, and so far the only, country in the world to legally mandate, subject to monitoring and penalties for non-compliance—CSR. This legal aspect, along with the potentially very large size (in financial terms) of the CSR “market”, creates several key challenges for all CSR stakeholders. These challenges can be analyzed in the following broad categorical terms:

  • Macro-economic: Excessive liquidity (at least in the initial years of mandatory CSR) in the CSR “market” and all the attendant problems characteristic of excessive liquidity.
  • Micro-economic: Corporate entities having to deal with issues outside their core areas of expertise and core business processes.
  • Behavioral-economic: A combination of above two types of challenges, giving rise to adverse phenomena, such as CSR fraud or even CSR “fatigue” among employees at all levels, from the shop floor/cubicle to the C-Suite.

India Decision Management’s CSR Analytics methodology: A client success story

A Fortune 100 technology multi-national approached IDM with a mandate to

  • Identify the key drivers behind the data pertaining to their CSR program.
  • Estimate if the program processes were performing at peak efficiency and effectiveness.
  • Identify any signals of fraud or other forms of organizational drag in their CSR process.
  • Identify if the sectors/segments and beneficiaries of their CSR program were in line with CSR sectorial tends at national and regional levels.
  • Help streamline and rationalize their CSR program management processes.
  • Identify feasibility of and key parameters for predictive models for agile CSR management.

Instead of using vanilla CSR Analytics tools, IDM consultants chose to apply the unique CSR Analytics methodology to address the clients’ requirements. A fine-grained analysis was performed on data representing the choices and actions of employees who were part of the company’s CSR processes.

The key inferences from IDM’s unique methodology-based analyses were:

    • The flow of the company’s CSR proceeds, and the sectorial categories of beneficiaries, fit well with national trends in CSR allocations6.
    • Several measures of employee participation in and contributions to CSR programs conformed to the Pareto Distributuion7 which describes a variety of natural and sociological phenomena. This indicates that the company’s CSR programs had grass-roots, organic and natural dynamics within the socio-economic space represented by the company.
  • Team and group participation were more significant than individual participation. This evidence re-affirms the idea described in the previous section, that psychosocial and human dynamics are key drivers and success factors of CSR.
  • CSR activity on particular dates and months of the year indicated the natural rhythm of employee schedules, workloads and other time-related human factors.
  • Predictive models of the company’s CSR process can be built to enable agile, rational, evidence-based, data-driven management.

The company had jumped in size from around 8,000 employees to 12,000 employees in a span of 2 years. This explosive growth resulted in a change in the demographics of the employees. With a younger and more group-activity-oriented employee base, some CSR activities were redundant while some newer ones were coming to the forefront.

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The above insights from the analyses will enable the company to:

  • Embed IDMs CSR Analytics methodology into their CSR processes and tool chains. This will entrench a human-centric, bottom-up and grass-roots approach to CSR.
  • Make CSR communications between program managers and employees more topical, agile and responsive.
  • Modify existing CSR processes or institute new ones as needed, to make their data evidence-driven, for increased efficiency and ROI, as well as reduced fraud and other organizational drag.
  • Build predictive and decision support models, so that the company’s CSR programs can be managed in a data-driven, evidence-based and rational manner.
  • All of the above will enable the company to shape CSR from just an ad-hoc/legally mandated activity into an integral, organic part of the company’s DNA.

References:

  1. CSR in India: A Changing Landscape. KPMG Report [PDF], March 2014.
  2. Handbook on Corporate Social Responsibility in India. PWC-CII Report [PDF].
  3. Mandatory CSR spend to cost India Inc Rs 8,700 cr a yr Business standard, July 11, 2011.
  4. The Role of Human Resource Management in Corporate Social Responsibility. A Strandberg Consulting Report [PDF]. By Coro Strandberg.
  5. Beyond corporate social responsibility: Integrated external engagement. McKinsey & Co. Article. March 2013. By John Brown and Robin Nutall
  6. Education tops corporate social responsibility spends, community development next. Economics Times (Online Edition), 16th Nov 2014.
  7. Pareto Distribution. Wikipedia.

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Image courtesy: http://www.freedigitalphotos.net/ Stuart Miles

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