CSR Analytics: Quantifying the Human Dynamics of CSR

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.

CSR - happy employees and happy society

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

IDM’s unique blend of expertise in CSR analytics is already producing successful results for our clients. This article details a project on CSR program rationalization, undertaken by IDM for a Fortune 100 multinational corporation.

In this article we will

  • Take a brief look at the broad challenges arising from a mandatory CSR regime.
  • Briefly describe analytics software vendors and their solutions/tools available in the market to help companies deal with CSR related processes.
  • Identify a key issue—the human aspects—of CSR Analytics that existing solutions and tools address only partially, or not at all.
  • Introduce the IDM methodology that will help companies directly tackle the above key issue, to institute effective and efficient CSR programs.
  • Briefly describe a client story that illustrates the effectiveness of the IDM methodology.

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.

Commercial tools and services available to manage CSR processes

There is a wide range of software tools and consulting services available to help companies address and manage challenges related to CSR programs. In this short article we will not provide an exhaustive list, but just a list of the main categories of software CSR related tools and services:

  • Program design and implementation management. Basically these are project and program management tools and services, customized for CSR.
  • Certification and Compliance monitoring. In this category are tools and services that help companies adhere to CSR related standards like ISO 14001.
  • CSR Audit management tools and services.
  • Activity/vertical specific tools and services. Environmental and energy sustainability oriented CSR tools and services form a dominant segment.
  • External sources feedback analysis. These help a company receive, measure and analyze feedback on its CSR programs from external sources like stock market and social media.
  • Peer-to-peer comparative analysis. These tools and services help a company compare and analyze its own CSR performance with that of other companies similar to itself.
  • Beneficiary monitoring and feedback analysis. These tools and services help a company receive and analyze performance data from direct beneficiaries of its CSR programs.

Human dynamics of CSR—the missing link in CSR Analytics

As can be seen, the above categories of tools and services address only the macro- and micro-economic challenges of CSR analytics and program management. They address the behavioral-economics—essentially the human and organizational—aspects only partially or not at all.

Yet, CSR is a grassroots phenomenon that touches and impacts all levels and functional divisions within an organization: from the sales team to the back-office, from the cubicle to the C-suite. Even external stakeholders, such as public stock holders evaluate and reach at a human/emotional level to companies’ CSR “image”, even though their reactions eventually impact at a financial level.

As such, IDM believes that measuring and analyzing the human dynamics of CSR is as much or perhaps more important than merely the operational, legal, financial or compliance aspects. This experience based view of IDM is echoed among prominent CSR analytics4, 5 as well.

IDM realized the primary importance of human dynamics, strategically early into its business foray into CSR Analytics. IDM evolved a unique and effective methodology for CSR Analytics by

  • Customizing for CSR, IDM’s existing deep and diverse experience with BFSI Analytics, Non-Profit Analytics and HR Analytics, and
  • Combining the above with IDM’s expertise in Psychographic and Demographic analytics, and
  • Evolving a synergistic, holistic methodology that provides a 360 degree analytical view of the human dynamics that drive a company’s CSR programs towards success or failure.

The resulting IDM CSR Analytics methodology has already yielded significant success and ROI for clients, as typified by the below client success story.

IDM’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 that 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 articular 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 above insights from IDM’s analyses will enable the company to:

  • Embed IDMs unique 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 them data and 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.

Summary and Conclusion

IDM strongly believes in and advocates a human-centric, yet data driven and evidence based approach to managing corporate CSR programs. IDM possesses deep expertise in BSFI analytics, Non-profit analytics and HR analytics. Leveraging this experience, IDM has evolved a unique synergistic methodology for CSR Analytics. This has been field tested in a project for a Fortune 100 multinational, wherein IDM analyzed their CSR program data and helped rationalize the program.

Anyone interested in leveraging IDM’s proven expertise in CSR Analytics, can contact us via our web site www.indiadecisionmanagement.com.

In addition to CSR Analytics, IDM also provides software tools, consulting services and training in several other areas including Big Data, Machine Learning, Text Analytics and several subdomains of Data Science/Analytics. Our expertise in these areas extends across multiple verticals, including BFSI, Health Care, Education and E-learning, Retail, E-Commerce, Web Analytics, Sales and Marketing Analytics, HR Analytics, Social Media and many others.


  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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