Effective Impact Management and Measurement Reimagined



2nd Jun 2020

Effective Impact Management and Measurement Reimagined

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Effective Impact Management and Measurement Reimagined

Impact management practices that are better going forward, we envision this as well as greater investment effectiveness.

“If we want to seize this turbulent moment, we need to be bold, and we need to be big. The time is now, to change our relationship to money, to change what it means to invest truthfully, time to change capitalism, for better systems, for a better world.” – Sapna Shah - GINN

Institutional and private equity investors are becoming increasingly conscious of the social and environmental impact (and financial returns) of their investment decisions.

If we have learnt anything from the COVID-19 pandemic then it must be the importance of data. Daily millions of people turned into news broadcasts to understand infection rates, recovery rates and unfortunately death rates.

Flattening the curve became the shared global objective and news broadcasters reported daily on how the pandemic has taken root in countries, spread, peaked and then of course – started declining.

Fascinated by statistics, and the process of monitoring, measuring, managing and analyzing data has mesmerized millions of people and sets a perfect backdrop to emphasize the importance of impact management and measurement

During the pandemic, the importance of sharing data, combining data collection methods, benchmarking data across geographies, triangulating and synthesizing data between scientists and health authorities globally, has shown what can be achieved.

This was particularly evident in the case of the COVID-19 genome sequencing which allowed scientists globally to work together to find solutions much quicker.

In addition, enormous stimulus and support packages were announced by governments, and questions were being raised. Where is the money going? How is it being spent? What impact will it have? What good will it do? How will we be able to say (in two or three years) that this money was well spent?

  • Don’t you want to know how bailout packages to airlines/hotels/restaurants will be spent? Is this not the kind of data that will influence future markets and investments?

  • Don’t you want to know how the millions of philanthropic donations were spent? What the impact thereof will be on future health care, food security, poverty and rebuilding of communities?

  • Don’t you want to know how millions of social purpose organizations and enterprises benefited by pivoting, innovating, responding, and/or made a difference in education, food distribution, manufacturing of masks, hand sanitizers or even ventilators?

Again, this is the type of data that will drive not only development decisions in the future, but also and even more critically – investors preferences and governments’ policy decisions. 

Over the next few years, impact data will become critical as we all want to know that the collective efforts, in some way or another, have contributed to the betterment of society, the economy and the environment.

In 5 or 10 years we may want to look back and say, “The Sustainable Development Goals have been achieved as a result of the collective investments and measurement practices of all stakeholders.”

In this regard the practices of monitoring, evaluation, impact management and measurement, impact verification, certification as well as impact reporting will become much more important in the future.

Reframing our use of impact data even before COVID-19

Even before COVID-19 our world was increasingly dependent on big data and data science in every aspect of our personal lives as well as our economic, political and social systems. 

  • Troves of real-time information on many issues, such as the cost of food, availability of jobs, our health status, jumps in the incidence of illnesses, our mobility patterns, etc. are produced every time a purchase is made. An Uber is called, a meal is ordered, a doctor is visited or a tweet is posted.

  • The exponential growth of transactional, human-generated data is paralleled by an increase in information and analytical capacity unimaginable even a few years ago, making it possible to predict, assess and research changes on people and the planet as it is happening. 

  • Using data science, it is possible for social science researchers and evaluators to collect a vastly increased range and volume of data more easily, quickly, and economically. Also, the ability of big data allows us to study everyone in an entire population, rather than just a relatively small sample.

    This makes it possible to avoid many kinds of selection bias inherent in research and enables disaggregation of the sample to cover many different sub-samples and categories, critical for more sophisticated problem-solving.

  • The technologies and now-affordable infrastructure of data science also means that social research and evaluation studies can be conducted more rapidly and cheaply while advancing our understanding of the complexity and interconnectivity of social problems – allowing for learning about larger-scale issues.

Reassessing monitoring, evaluation, and impact measurement during COVID-19

During the COVID-19 pandemic we became aware that traditional ways of collecting, monitoring, evaluating and assessing data will need to change.  It had to change, quite simply because:

  • We could not collect data in person anymore because of limitations and restrictions on the movement of people and we could not use traditional activity-based monitoring methods due to possible transmission and infection risks.

  • We could not wait for data to be collected, documented, analyzed, and verified, as we needed real-time analysis and on-demand reporting.

  • We could not collect data in isolation: We needed the technology and capacity to combine and integrate various data sets at great speed, such as satellite or drone images, household survey data, program administrative data, social media analytics, phone/call-centre data, information generated through mobile phones and internet search and more.

  • We needed to combine data sources: Across dispersed geographical areas, integrate data across health, economic, demographic data sets and track and trace individuals and their personal data sets both instantaneously as well as over time.

    This makes it possible to understand data in different and big picture contexts, in ways that was previously not possible.

  • And we needed the computing speed of cloud-based, big data architectures and data techniques like machine learning algorithms to create an integrated toolkit for almost instantaneous findings and insights.

  • Probably most important of all, we needed to be able to interpret, collate, synthesize and triangulate the data quickly and transparently. This can result in informed decisions that could be made much quicker, lessons learnt could be documented, case studies developed to share across sectors, geographies and disciplines/sectors to inform immediate pandemic responses.

Rewiring impact management and measurement post COVID-19

Whilst none of us have a clear view of what the new world will look like, we do know that there are some practices that we do not want to take with us into this new world. We are also keenly aware how our shortcomings will show up in the future, and therefore we need nothing short of an impact revolution. 

And whilst many impact management and measurement challenges have already been identified by investors and practitioners in the field of impact management and measurement, we also need to recognise that the time has come to move past the ongoing debates around the lack of standardization, as well as long-winded discussions around universal metrics.

We know that impact investing and impact management and measurement are two sides of the same coin and are completely interdependent. The success of impact investing will depend completely on the ability of impact investors to provide evidence of the impact achieved by their investments.

Measuring impact is far from a trivial task, therefore we will need to look towards a future where we:

  1. Solve the issue of causality:  Investors in the future will need to know if the impact observed/measured and verified were caused by their own effort instead of other confounding factors. In other words, what would have happened if the investment were not made or intervention not implemented in the first case?

  2. Solve the issue of comparability: In traditional strategy research, economic performance is measured using standard indicators, such as return on assets or stock market value and compared to a common norm such as average industry performance. But how to contrast the outcomes of investments covering distinct areas such as education, health or crime prevention.

    Or, measure the difference in outcomes of investments in developing or frontier markets. Or, how to measure the outcomes of an investment across portfolios such as renewable energy or housing will be critical.

  3. Solve the issue of complexity:  We need to recognise that impact does not happen in a neat linear fashion. For every positive impact there is also a negative impact, whether intended or not. 

    Similarly, for every intended impact there is also unintended impact. The ability to measure and verify this impact across ecosystems and stakeholder groups need to be addressed with deep insight.

However we solve these challenges, it is our wish that a world post COVID-19 will bring about greater investment effectiveness as well as better impact management practices.

In addition, that we don’t get stuck in our quest for a universal standard, but that we also address the issues that until now have been neglected from the collective action. May investors in the new world after COVID-19 focus on one thing only – to do whatever it takes to ensure a fair, inclusive, equitable future for all of humanity.


 

Impact ManagementRECOMMENDED READING: Reimagining The Future of Impact Management, Measurement & Evaluation


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