The Whizbang Weekly

AI’s Bottom Line: Decoding the Cost-Benefit Matrix of Gen AI

Campbell Robertson

As generative AI technologies continue to potentially reshape industries, technical executives face the daunting task of harnessing their potential while mitigating risks. The key to success lies in developing a comprehensive business plan that accurately measures the impact of these technologies on your organization.

Over the years I have helped many customers assess the tangible ROI, NPV, etc. metrics in making decisions about technology as well as the longer term benefits. Gen AI technology is not any different, because at the end of the day Gen AI or Agentic AI is a data project. The key factor is not only looking at the hard numbers in your plan but the intangibles: Benefit and Risk when it comes to you business but also the technical aspect of running your business. Intangibles touch on many things that are important to you and your organization: People, Process and Policy. If you want to discuss more around how to do this, let me know. But for now lets take a look at some of the basics.

This approach works if you are looking at moving off of “status quo” or comparing offerings and solutions from various vendors. This would be applied to GenAI, Databases, or any technology. Remember I am all about future proofing the decisions that you make.

Here’s how to approach making a business case:

Establishing Relevant KPIs

To effectively gauge the success of your generative AI initiatives, start by aligning your Key Performance Indicators (KPIs) with your organization’s strategic objectives. Look to industry benchmarks and reports from reputable sources like McKinsey, Gartner, and KPMG for sector-specific metrics. Common KPIs include:

  • Operational efficiency (e.g., process times, error rates, automation levels)
  • Customer satisfaction (e.g., Net Promoter Score, Customer Satisfaction Score)
  • Revenue generation and profitability
  • Productivity gains
  • Innovation metrics (e.g., time-to-market for new products)

Several industry KPI databases are available for accessing comprehensive sets of key performance indicators across various sectors:

Umbrex KPI Library

Umbrex offers a downloadable spreadsheet containing over 1,600 Key Performance Indicators across 32 industries. This extensive library covers a wide range of sectors, including:

  • Aerospace & Defense
  • Agriculture
  • Automotive
  • Financial Services
  • Healthcare
  • Manufacturing
  • Technology
  • Telecommunications

The KPI Institute’s Smartkpis.com

Smartkpis.com, managed by The KPI Institute (TKI), is one of the world’s largest KPI databases. It features:

  • 21,264 documented KPIs
  • Coverage of 25 industries and 16 functional areas
  • Access for over 84,000 subscribers

The database includes KPIs for various contexts, including business environments, global metrics, and even personal productivity measures.

Flevy KPI Library

Launched in November 2023, the Flevy KPI Library is a comprehensive database containing 15,263 High Performance Key Performance Indicators. It offers:

  • KPIs across various industries and functions
  • Detailed descriptions for each KPI
  • Potential business insights
  • Measurement processes
  • Standard formulas

This resource is designed to enhance strategic decision-making and performance management for executives and business leaders.

The KPI Institute’s Industry KPI Dictionaries

The KPI Institute also offers industry-specific KPI dictionaries. These resources provide:

  • Comprehensive collections of KPIs specific to particular industries
  • Tools for implementing sound performance measurement and management systems
  • Guidance on selecting critical KPIs to drive organizational success

Accessing These Databases

To access these KPI databases, you typically need to:

  1. Visit the respective websites
  2. Choose a subscription plan that suits your needs
  3. Register for an account
  4. Log in to access the KPI libraries

Some of these resources may offer free trials or limited access to sample data before requiring a paid subscription.

By utilizing these industry KPI databases, you can gain valuable insights into performance metrics relevant to your specific sector, enabling more effective benchmarking and strategic decision-making for your organization.


Calculating ROI: Beyond the Numbers

When calculating Return on Investment (ROI), it’s crucial to look beyond immediate financial gains. Consider both tangible and intangible benefits:

  1. Tangible Benefits: Quantify cost savings, revenue increases, and productivity improvements directly attributable to generative AI implementation.
  2. Intangible Benefits: Assess improvements in decision-making quality, employee satisfaction, and market competitiveness.
  3. Long-term Impact: Factor in the potential for generative AI to create new revenue streams or transform business models.
  4. Cost Considerations: Include not only initial implementation costs but also ongoing expenses for data management, model updates, and staff training.

Composite Scoring: Balancing Benefits and Risks

To create a holistic view of your generative AI initiatives, develop a composite score that weighs both benefits and risks across business and technical dimensions:

Business Benefit and Risk

  • Benefit: Evaluate potential market share growth, customer retention improvements, and operational efficiencies.
  • Risk: Consider data privacy concerns, potential bias in AI outputs, and regulatory compliance issues.

Technical Benefit and Risk

  • Benefit: Assess improvements in system performance, scalability, and integration with existing infrastructure.
  • Risk: Evaluate cybersecurity vulnerabilities, model degradation over time, and dependency on specific AI platforms.

Assign weighted scores to each factor based on their importance to your organization. This composite approach provides a nuanced understanding of the overall impact of generative AI on your business.

Building a Robust Business Plan

With these metrics in hand, craft a business plan that:

  1. Sets Clear Objectives: Define specific, measurable goals for your generative AI initiatives.
  2. Prioritizes Use Cases: Focus on high-impact areas where generative AI can deliver significant value.
  3. Outlines Implementation Stages: Develop a phased approach, starting with pilot projects and scaling based on success.
  4. Addresses Governance: Establish frameworks for responsible AI use, including ethical guidelines and risk management protocols.
  5. Plans for Continuous Evaluation: Implement systems for ongoing monitoring and adjustment of your generative AI strategy.

As you embark on this journey, remember that the true value of generative AI often emerges over time. While immediate gains are important, the transformative potential of these technologies may take longer to fully materialize. By establishing a comprehensive measurement framework and maintaining a balanced perspective on benefits and risks, you’ll be well-positioned to lead your organization through the generative AI revolution.

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