How AI helped Formulating Energy-Efficiency Strategy

A case study that examines the use of AI to generate strategy with goals, KPIs, and initiatives using general information about the company, initial prompt for strategy, and follow-up clarification prompts.

Introduction

At the beginning of 2025, XYZ Eco Group faced the challenge of improving energy efficiency due to rising energy costs. To identify and describe an appropriate response strategy, they used the AI functionality in BSC Designer.

Results: AI-Generated Strategy Map

Here is a strategy map generated by discussing the challenges of energy efficiency with AI:

AI-generated strategy map for achieving energy efficiency

The strategy map was automatically generated by BSC Designer using AI-generated data on goals, KPIs, and initiatives from the KPIs tab:

Structure of goals, KPIs, and initiatives generated by AI

Below, we review the prompts used step by step.

Preparation

Energy efficiency strategy scorecard

Some preparation steps were taken:

  • A new strategy scorecard (Energy Efficiency Strategy) was created to separate the energy efficiency strategy from the main strategy.
  • The required contextual information about the company was already specified on the Settings > Strategy tab.

Initial Strategy Formulation

The company began with a general prompt to AI:

Prompt: Let’s develop a strategy for our company focused on achieving energy efficiency.

The Balanced Scorecard perspectives were not used in the first response.

The response included reasonable suggestions, but they were not formulated according to the Balanced Scorecard framework used by the company. To address this, a clarification request was made:

Prompt: Utilize the existing perspectives of the Balanced Scorecard framework provided in the template.

This time, AI responded within the required framework:

AI-generated items added to the scorecard

By clicking the “Execute all” button, all suggested goals were added to the scorecard.

Improving Goals in the Learning Perspective

A follow-up question about learning-related goals was asked:

Prompt: The ‘Energy Efficiency Training Programs’ goal in the Learning Perspective addresses existing technology, but how about also focusing on identifying new energy-saving opportunities?

AI responded with reasonable suggestions, but mistakenly placed them under the existing ‘Energy Efficiency Training Programs’ goal. A follow-up prompt was issued:

Prompt: The suggestions sound more like something we can do in parallel with ‘Energy Efficiency Training Programs’—let’s incorporate them accordingly into the Learning Perspective.

This time, the goals and initiatives were correctly formulated in the Learning Perspective:

AI added new learning goals to the Learning and Growth perspective

Additional Goal for Internal Perspective

In another follow-up question, AI was asked to cover an additional goal in the Internal Perspective:

Prompt: For internal processes, we have an optimization goal, but how about incorporating renewable energy sources, such as solar power?

The AI response was approved, and the software immediately visualized it on the strategy map:

AI response visualized on the strategy map

Adding More Specific KPIs

The “Integrate Renewable Energy Sources” goal was quantified with a general “Amount of Energy Generated by Solar Power” indicator. To make it more specific, AI was asked to suggest additional KPIs:

Prompt: For ‘Integrate Renewable Energy Sources,’ we can also track the specific amount of energy generated through solar power.

AI responded with a suggested KPI and one initiative:

Response of AI on adding additional KPIs
Once approved, the KPIs were automatically added to the KPIs tab:

KPIs generated by AI were approved and added to the KPIs tab structure

Adding Sub-Goals to the Goal

With the next prompt, AI was asked to be more specific about a goal and add more details:

Prompt: The goal ‘Customer Awareness on Energy Efficiency’ sounds like a high-level, aspirational objective. Let’s make it more specific by adding sub-goals with clear KPIs.

Sublevels of KPIs were added to make the goal more specific:

AI makes the goal more specific by adding sublevels of KPIs

AI Asks Follow-up Questions

Finally, a dialog mode for AI was triggered with this prompt:

Prompt: In ‘Energy Cost Reduction,’ we track direct cost savings. Are there any indirect cost savings? We’re not sure, so ask me 1-2 questions about our business to help determine if there are additional metrics we can track.

AI asked relevant questions and began analyzing the answers:

AI asked questions to help formulate the KPIs

The suggestions provided by AI were incorporated into the scorecard:

Suggestions from the dialog with AI were added to the scorecard

Cite as: BSC Designer, "How AI helped Formulating Energy-Efficiency Strategy," BSC Designer, December 21, 2024, https://bscdesigner.com/energy-efficiency-strategy-with-ai.htm.

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