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8 Major Challenges in M&E and How to Overcome Them

Challenges in M&E and How to Overcome Them image

8 Major Challenges in M&E and How to Overcome Them

Even though many INGOs and organizations have monitoring and evaluation software, it’s common for it to be built on a results-based framework. The results-based framework emphasizes project management, stressing gathering activity and output results, and is frequently closely connected between several initiatives. These systems face difficulties with monitoring and evaluation because they are frequently either too complex or too simplistic to effectively manage activities and produce outcomes. Either they concentrate on straightforward data gathering, visualizing, or recording, or some are smart but unnecessarily complex, require a long time to implement, and are hard to improve once they’re in place. Most monitoring and evaluation methods fall short of offering scalable answers to regularly aggregate results. For those that do, extensive modification or manual data aggregation may be necessary.

Without further ado, let’s look at the eight worst mistakes to steer clear of when selecting monitoring and evaluation systems. This article will outline the most typical monitoring and evaluation challenges and provide comprehensive strategies to solve them.

  1. M&E is a luxury

There is a misconception in the field of social impact that impact measuring is a luxury and a necessary evil to appease a donor. Some social entrepreneurs will throw the kitchen sink at you like this;

  • Since we already know that we are contributing to society, why do we need to measure?
  • We are a young social organization barely scraping together a business plan; measuring is an unneeded burden.
  • No one is paying for impact measurement.

Most of these arguments are so self-serving or show a lack of grasp of impact measurement’s underlying principles.

  1. Lack of confidence in the data

Despite the fact that billions of funds are being spent at the direction of donors, the majority of reporting data is only gathered because board members or congressmen mandate that all foundations and foreign development projects submit reports. Many of these program organizations spend a lot of time and money on RCT, survey data collection, etc. Despite being a necessary evil, this does little to build donors’ trust.

Funders (asset owners, asset managers) and organizations that deal closely with the stakeholders might better align their interests by setting higher standards for impact management practices. To improve stakeholder-aligned impact, this method calls for a culture of impact & result alignment, a better impact measurement language, and consensus on enhancing data culture. This is arguably the biggest waste of valuable resources and the most overlooked factor in the lack of data trust.

3.  Lack of change-driven theory of data collection

Most firms lack a solid data strategy or don’t gather any data at all. If they are gathering data, they frequently pay attention to activity and output data, which typically do not fit with and validate the organization’s fundamental mission and vision. The biggest obstacle to comprehending social change is the misalignment between the theory of change and data collecting. An organization cannot grasp WHAT, WHO, CONTRIBUTION, HOW MUCH, and RISK without this alignment, which is a necessary condition for comprehending and communicating social impact.

Make sure the process is practical and effective.

THEORY OF CHANGE (TOC) TO Theory Of Action Theory of Change (ToC) outlines the causal links in an effort and describes your organization’s intended path to impact (i.e., its shorter-term, intermediate, and long-term outcomes). Theory of Action outlines a practical strategy to increase social impact.

4.  Simple data aggregation and data islands

The data gathering system is in line with the theory of the change-based approach to better understand program outcomes or results.

  • Where do you gather information on output and activity?
  • Are all of these facts present?
  • What is the main result you hope to achieve?
  • How can you tell if the change you are making is the appropriate one?
  • How can you quickly get results and gain insightful knowledge?

The problem here is that the data collecting and program management systems of most firms are disorganized. Many businesses continue to collect data using MS Excel, Google Spreadsheets, or customized database programs. Although spreadsheet-based solutions based on MS-Excel and Google are simple to set up and understand, they impose significant challenges;

•         Without effective data management, firms over time develop data islands, which makes it challenging to follow data.

•         Impact framework and measures are subject to yearly change, which makes data management difficult.

•         Even within Excel, someone must integrate the data and reapply the formula following each event or field data collection, which adds a lot of errors and time.

•         Excel lacks a fundamental understanding of the principle of change, hence not the best analytics platform.

In the end, a typical business uses 4 to 6 distinct methods to accomplish all of the impact measurement goals, increasing time and resource waste significantly.

  • Analytics & Lean Data Measurement

Using scalable lean data measurement and analytics by integrating standardized outcome and evidence libraries, theory of change, and data alignment can help overcome this challenge. It helps to make impact evaluation and management simple by superseding methods based on MS-Excel and Google Sheets.

  1. A weak impact framework makes it difficult to show the impact.

You are more likely to start with one of the many frameworks available—including outcome and impact frameworks—and adjust it to suit your organization’s needs. The ideal framework is one that frequently aids in bringing together various effect ecosystem actors. But where do you begin right now?

Despite the emergence of new global reporting frameworks like the Sustainable Development Goals (SDG) and IRIS, most businesses lack the ability to integrate all of their internal theory of change or measurement goals with global standards and structure.

6. Stakeholders’ voices not being heard when measuring social impact

Impact measurement’s main goal is to improve the beneficiary’s situation. Exactly who are our stakeholders? Stakeholders are people who have an impact on and are impacted by your actions. Do you, however, have a method that conveys the happiness or dissatisfaction of stakeholders over their user experience?

  • Do we believe that disclosing the number of beneficiaries served makes sense?
  • Is it appropriate to disclose the number of meals served to children when their requirements frequently outweigh available interventions?

Don’t brag about how many recipients benefited from the solar lantern; instead, focus on the fundamental questions that need to be addressed. Discuss how many of them are content or unhappy with a recent purchase.

•         Do they appear to be happy with their jobs?

•         Will the new financing program actually lead to better results?

  1. Communicating the impact of donor funding is difficult

Lack of visibility between financing and actual impact is the biggest obstacle for donors when making decisions.

  • Shorten the data distance by improving beneficiary and stakeholder voices.
  • Data analytics powered by AI and integrated with an impact scorecard.
  •  Provide distributed and unconnected hierarchical organizations with large-scale data integration to close the gap between donor and stakeholder.
  •  Create the best impact evidence strategy.

8. Customization is expensive, restrictive, time-consuming, and difficult.

The impact ecosystem requires considerably more extensive and scalable solutions than its corporate equivalents. The sum of all the aforementioned obstacles is that we can only have a theory of change-led effect measurement with fewer resources and all the stakeholders at the same table if we have a flexible, comprehensive, adjustable system.

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