top of page

Using logic models in go/no-go decisions

For organizations, deciding whether to bid on a project can be fraught with complexity and subjectivity. Business development professionals often face the challenging task of balancing the enthusiasm of country or technical teams with a realistic assessment of the organization's capabilities. How can you make informed go/no-go decisions that everyone respects and understands? This blog introduces a logic model based on the fuzzy sets theory and provides a more nuanced way to assess project suitability.


What Are Fuzzy Sets?

Fuzzy sets are a concept developed by Lotfi A. Zadeh in 1965 as part of fuzzy logic theory, which is designed to handle the kind of uncertainty and imprecision that traditional binary logic (yes/no, true/false) struggles with. In essence, fuzzy sets allow for graded membership rather than binary classification. This means that an element can belong to a set to a certain degree, ranging from 0% (completely does not belong) to 100% (fully belongs).


The Science and Research Behind Fuzzy Sets

Fuzzy sets theory is underpinned by solid mathematical principles and has been supported by extensive research over the decades. It’s widely used in fields where decision-making involves uncertainty and subjective judgments, such as engineering, economics, and environmental management. Studies have shown that fuzzy sets provide a flexible framework for incorporating human-like reasoning in decision processes, making it highly relevant for go-no-go decisions.


Applying Fuzzy Sets to NGO Decision-Making

Step-by-Step Application:

  1. Define Criteria: List the necessary skills and resources required for the project, such as technical expertise, local knowledge, or specific logistical capabilities.

  2. Assess Capabilities Using a Fuzzy Scale: Evaluate your organization’s capabilities against these criteria using a scale that reflects degrees of expertise:

  • 0 (no capability)

  • 0.25 (limited capability)

  • 0.5 (moderate capability)

  • 0.75 (strong capability)

  • 1.0 (full capability)

  1. Aggregate and Weight Scores: Combine the scores for each criterion, considering the importance of each criterion. Weighting each criterion reflects its significance relative to the project’s success, ensuring that more critical aspects have a greater impact on the decision.


Real-World Application

Imagine your NGO is considering a bid for a health education project in a region where you have some presence. The main criteria might be:

  • Local Knowledge: Essential for cultural sensitivity and effectiveness.

  • Health Education Expertise: Crucial for delivering accurate information.

  • Logistical Capability: Important for reaching remote areas.

If your team’s local knowledge is strong (0.9), your health education expertise is moderate (0.5), and logistical capability is somewhat limited (0.3), and you weight local knowledge and expertise higher than logistics, the fuzzy aggregate score might still justify a bid, given the high importance and strength in critical areas.


The Importance of Weighting Criteria

Weighting criteria is crucial because it aligns the decision-making process with strategic priorities. It ensures that the areas most critical to project success have a proportionate influence on the overall assessment. This helps prevent less important factors from disproportionately affecting the decision, which is particularly important in complex environments where not all capabilities are equally important.


Bridging the Subjectivity Gap

To address the inherent subjectivity and internal competition:

  • Calibration Meetings: Regularly hold meetings to discuss and align on what each level of capability truly means in the context of the NGO’s mission and project goals.

  • External Benchmarks: Compare your team’s skills against industry standards to gauge where you really stand.

  • Transparent Communication: Keep all stakeholders informed about the decision-making process and the rationale behind each decision. This builds trust and understanding.


Handling Disagreements

Disagreements are inevitable, especially when teams are passionate about their potential to secure and deliver projects. Here are a few tips to manage such situations:

  • Data-Driven Discussions: Base your discussions on data from past project performances and objective assessments. This can help shift the conversation from opinions to facts.

  • Incremental Engagement: If feasible, consider taking on smaller components of a project to test capabilities in a real-world setting before fully committing.

  • Consultative Approach: Engage in discussions rather than dictating decisions. Explore why teams feel ready to take on the project and address any misconceptions with evidence.


Leveraging Advanced AI for Smarter Decision-Making

GPT: BidMaster AI, Go No GO Assistant

Bid Master AI is an innovative tool that runs on ChatGPT 4.0 designed to streamline the bid/no-bid decision-making process for organizations. By using the principles of fuzzy sets theory along with weighted lists, this tool helps manage the inherent uncertainties and subjective judgments involved in determining the viability of pursuing a project. By incorporating fuzzy logic, Bid Master AI allows organizations to input qualitative assessments—such as potential project impacts, team capabilities, and resource availability—which are then translated into fuzzy numbers. These numbers represent degrees of confidence in each criterion, rather than absolute yes or no answers. This approach enables a more nuanced and flexible evaluation process, where different factors are weighted according to their importance to the overall decision. The final output is a "fuzzy possible success rating," which gives decision-makers a probabilistic understanding of project success, making the bid/no-bid process both more dynamic and informed. This use of fuzzy sets ensures that Bid Master AI can adapt to complex and often fluctuating business landscapes, providing organizations with a robust tool to enhance their bidding strategies.




16 views0 comments

Comments


bottom of page