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landscape, retailers are feeling the pressure to optimize their inventory management practice. With fluctuating customer demand, fast-paced market disruptions, complex supply chains, and rising costs, traditional inventory management practices are becoming increasingly inadequate. To stay competitive, retailers must embrace and implement new technology that allows them to stay ahead of the competition.</p> <p>Inventory management applications that are AI-driven can deliver where traditional inventory management falls short, by providing real-time insights backed by big data, enabling retailers to respond to market changes through predictive forecasts that reduce waste, improve operational efficiency, and enhance customer satisfaction. </p> <p>While most retailers understand the potential of AI, most lack the clarity of where to start, what to adopt, and how to scale, to take advantage of the competitive edge that AI provides. This research piece provides clarity around AI in inventory management and use cases and offers a step-by-step guide to help retailers build out a robust and actionable AI use case library for inventory management.</p> <p><img src="https://cdn1-public.infotech.com/blueprints/Build-Your-AI-Strategy-for-Retail-Inventory-Management-Storyboard/donnafay-macdonald.png" loading="lazy" width="223" height="223" alt="A picture of Donnafay MacDonald"></p> <p><strong>Donnafay MacDonald</strong><br> Research Director, Retail Industry Practice<br> Info-Tech Research Group</p> </section> <section> <h2>Executive summary</h2> <h3>Your Challenge</h3> <p><strong>Develop a business-driven AI strategy to improve inventory management</strong> that minimizes the risks associated with an AI-based solution. </p> <p><strong>Understand the potential opportunities and risks to improving business outcomes </strong>and best practices when developing or deploying an AI-driven inventory management application.</p> <p><strong>Assess the organization's capabilities to provide a data platform </strong>that is optimized for analytics and inventory management and would support new technology infrastructure.</p> <h3>Common Obstacles</h3> <p><strong>Getting the right business stakeholders together to develop an AI strategy </strong>that addresses inventory management limitations and understands the gaps the organization needs to address to fully leverage AI.</p> <p><strong>Prepare and understand the benefits associated with AI, </strong>which often requires mature data and system capabilities.</p> <p><strong>Advancing existing business and human-based requirements</strong> to adopt AI-driven applications.</p> <h3>Info-Tech's Approach</h3> <p><strong>Guide business leaders through identifying and prioritizing AI use cases</strong> for their business capabilities through a benefits realization model to start their AI journey. </p> <p><strong>Leverage the output to gain executive buy-in to rapidly </strong>and responsibly implement AI, referencing use cases that can provide the greatest value to address your organizational challenges and meet business goals.</p> <p><strong>Develop an AI strategy use case roadmap for retail inventory management that becomes </strong>a strategic path forward that effectively and efficiently accelerates adoption.</p> <h3>Info-Tech Insight</h3> <p>Retailers need to adopt an AI-driven inventory management system to stay competitive in an industry where competitors are using AI to run the core operations of their organizations.</p> </section> <section> <h2>It is essential to mitigate the challenges of traditional inventory management</h2> <p><strong>Traditional inventory management practices in retail have limitations </strong>and primarily focus on two key parameters: (1) the process of ordering product, and (2) carrying buffer stock to meet demand. In addition, the management systems used are often restrictive with low product visibility, limited flexibility, and lack of robust data analytics. This leads to inefficient operations and higher costs of doing business.</p> <p><strong>Retailers often misjudge product demand </strong>due to the use of disparate systems in complex supply chains which adds the challenge of working with fragmented data in outdated tools, such as Excel, leading to inaccurate forecasts, missed sales opportunities, dissatisfied customers, and unnecessary costs to the organization.</p> <p><strong>The underlying challenge is the rigidity of traditional inventory management </strong>where it is unable to adapt quickly to changes in sudden market shifts, unexpected disruptions, and changes to trends and customer behavior. Ultimately, the challenges of traditional inventory management practices leaves retailers less competitive. </p> <p>"In the intricate world of business operations, mastering inventory control is not just a necessity – it's the key to unlocking operational excellence." <br> Source: Supply Chain 24/7, 2024.</p> <h3>Traditional Inventory Management Challenges</h3> <ul> <li>Lack of Visibility</li> <li>Lack of Data Analytics</li> <li>Integration Issues</li> <li>Lack of Flexibility</li> <li>Complexity</li> <li>Overstocking and Understocking</li> </ul> </section> <section> <h2>Misjudged product demand increases retailer losses</h2> <p>"Forecasting accuracy is a crucial factor for any business that relies on predictions of future events, such as demand, sales, revenue, costs, risks, or opportunities." </p> <p>Source: FasterCapital, 2024.</p> <table width="900" border="1"> <tbody> <tr> <th scope="col"><p>Lost Customers</p></th> <th scope="col"><p>Lost Global Revenue</p></th> <th scope="col"><p>Increased Cost</p></th> </tr> <tr> <td align="center"><p><strong>91%</strong></p></td> <td align="center"><p><strong>8.3%</strong></p></td> <td align="center"><p><strong>43%</strong></p></td> </tr> <tr> <td><p>of consumers will choose not to shop with a retailer after a negative experience.</p></td> <td><p>of global retail revenue is lost due to out-of-stock items, amounting to an estimated $1.75 trillion annually.</p></td> <td><p>of retailers face increased costs in the supply chain because of stockouts.</p></td> </tr> </tbody> </table> <p>Source: Tools Group, 2024.</p> </section> <section> <h2>Lead with value by aligning AI initiatives to business needs</h2> <p>"AI projects should come from a value-led position rather than being led by technology. The key is to always ensure you know what value you're bringing to the business or to the customer with the AI." </p> <p>– Alex Sidgreaves, Chief Data Officer at Zurich Insurance, quoted in MIT Technology Review, 2024</p> <table width="900" border="1"> <tbody> <tr> <th scope="col"><p>Leverage AI to Enhance Operations</p></th> <th scope="col"><p>Improve Inventory Management With AI</p></th> </tr> <tr> <td align="center"><p>51%</p></td> <td align="center"><p>72%</p></td> </tr> <tr> <td><p>of retail and consumer package goods executives state they are using AI in their operations.</p></td> <td><p>of AI implementations in physical stores is being used for inventory management.</p></td> </tr> </tbody> </table> </section> <section> <h2>AI overview</h2> <p><img src="https://cdn1-public.infotech.com/blueprints/Build-Your-AI-Strategy-for-Retail-Inventory-Management-Storyboard/deep-learning-ai.png" loading="lazy" width="200" height="200" alt="Deep learning - Machine Learning - Artificial Intelligence."></p> <h3>Definitions</h3> <p><strong>Artificial intelligence (AI) </strong>is human intelligence mimicked by machine algorithms. Examples: playing chess or Go.</p> <p><strong>Machine learning (ML)</strong> is a subset of AI algorithms to parse data, learn from data, and then make a determination or prediction. Example: spam detection, preventative maintenance.</p> <p><strong>Deep learning (DL)</strong> is a subset of machine learning algorithms that leverage artificial neural networks to develop relationships among the data. Examples: image classification, facial recognition, generative AI.</p> <h3>What Makes AI Perform</h3> <p>Algorithms</p> <p>Accelerators</p> <p>Big Data</p> <h3>What Makes AI Different</h3> <table width="607" border="1"> <tbody> <tr> <th width="297" scope="col"><p>Traditional Programming</p></th> <th width="294" scope="col"><p>Machine Learning</p></th> </tr> <tr> <td><img src="https://cdn1-public.infotech.com/blueprints/Build-Your-AI-Strategy-for-Retail-Inventory-Management-Storyboard/traditional-programming.png" loading="lazy" width="297" height="58" alt="An image of the formula for Traditional Programming"></td> <td><img src="https://cdn1-public.infotech.com/blueprints/Build-Your-AI-Strategy-for-Retail-Inventory-Management-Storyboard/machine-learning.png" loading="lazy" width="298" height="60" alt="An image of the formula for Machine Learning"></td> </tr> </tbody> </table> </section> <section> <h2>Design value-driven outcomes with an AI strategy for inventory management</h2> <p>Building out an AI strategy for retail inventory management involves linking AI capabilities to the strategic sources of value of the retail organization. AI adoption should focus not only on technology adoption but also on what real business problems are being solved and the value being created. Below is a list of the strategic sources of value and operational sources of value to consider when building out your AI strategy for retail inventory management.</p> <p>Retailers adopting AI in inventory and supply chain management have seen up to 48% optimization gains. </p> <p>Source: Nvidia, 2025</p> <table width="900" border="1"> <tbody> <tr> <th valign="top"><p><strong>Strategic Sources of Value</strong></p></th> <th valign="top"><p><strong>Description</strong></p></th> </tr> <tr> <td valign="top"><p><strong>Operations Efficiency</strong></p></td> <td valign="top"><p>Reducing costs through operational performance improvements.</p></td> </tr> <tr> <td valign="top"><p><strong>Customer Experience</strong></p></td> <td valign="top"><p>Improving customer experience with a product/service through reliability, engagement, transparency, etc.</p></td> </tr> <tr> <td valign="top"><p><strong>Business Growth</strong></p></td> <td valign="top"><p>Expanding the organization's products/services/ capabilities to ultimately drive revenue expansion or customer impact.</p></td> </tr> <tr> <td valign="top"><p><strong>Employee Experience</strong></p></td> <td valign="top"><p>Optimizing the employee experience through changes that make work easier and more enjoyable, thus increasing job satisfaction.</p></td> </tr> <tr> <td valign="top"><p><strong>Risk & Resilience</strong></p></td> <td valign="top"><p>Mitigating diverse risk, health, safety, and continuity of operations concerns to preserve stable and sustainable performance.</p></td> </tr> <tr> <td valign="top"><p><strong>Environment, Social & Governance (ESG)</strong></p></td> <td valign="top"><p>Improving environmental impacts, social and community wellbeing, and corporate governance practices.</p></td> </tr> </tbody> </table> <table width="900" border="1"> <tbody> <tr> <th valign="top"><p><strong>Operational Value Outcomes</strong></p></th> <th valign="top"><p><strong>Description</strong></p></th> </tr> <tr> <td valign="top"><p><strong>Reduced Costs, Waste, and Spoilage</strong></p></td> <td valign="top"><p>AI-powered forecasting, allocation, and replenishments reduce overstock, spoilage, and obsolescence.</p></td> </tr> <tr> <td valign="top"><p><strong>Improved Profit Margins</strong></p></td> <td valign="top"><p>Precise inventory management and data-driven product allocations improves overall inventory position.</p></td> </tr> <tr> <td valign="top"><p><strong>Increased Operational Efficiency</strong></p></td> <td valign="top"><p>Streamlined supply chain using AI and automation leads to efficient operations and faster inventory turns.</p></td> </tr> <tr> <td valign="top"><p><strong>Faster Response to Market Changes</strong></p></td> <td valign="top"><p>Real-time date and predictive insights helps retailers quickly adjust and adapt inventory strategies.</p></td> </tr> <tr> <td valign="top"><p><strong>Improved Supplier Relationships</strong></p></td> <td valign="top"><p>Informed AI-driven demand forecasts allows for more reliable planning, fostering stronger partnerships and better inventory.</p></td> </tr> <tr> <td valign="top"><p><strong>Enhanced Customer Satisfaction</strong></p></td> <td valign="top"><p>AI-driven product allocation ensures the right product is available at the right time. </p></td> </tr> </tbody> </table> </section> <section> <h2>Value outcomes from AI-driven inventory management applications</h2> <h3>Visual representation of an AI inventory management data and decision-making flow</h3> <p><img src="https://cdn1-public.infotech.com/blueprints/Build-Your-AI-Strategy-for-Retail-Inventory-Management-Storyboard/ai-inventory-management-data.png" loading="lazy" width="700" height="246" alt="Visual representation of an AI inventory management data and decision-making flow"></p> <h3>Value Outcomes</h3> <ul> <li>Reduced Costs, Waste, and Spoilage</li> <li>Increased Operational Efficiency</li> <li>Improved Supplier Relationships</li> <li>Improved Profit Margins</li> <li>Faster Response to Market Changes</li> <li>Enhanced Customer Satisfaction</li> </ul> <p>"Without proper tools and processes for managing data, enterprises will find themselves at a severe disadvantage in an AI-first economy that is fueled by data. A seamless, end-to-end analytics platform empowers procurement and supply chain with AI-driven insights, centralized data management and self-service capabilities, unlocking agility, cost efficiency and informed decision-making." <br> Source: GEP Intelligence, 2024<br> Source: LeewayHertz, 2025</p> </section> <section> <h2>Maximize retail success through effective inventory management principles</h2> <table width="900" border="1"> <tbody> <tr> <td><p><strong>Principles</strong></p></td> <td><p><strong>Summary</strong></p></td> <td><p><strong>Advantages</strong></p></td> <td><p><strong>Disadvantages</strong></p></td> <td><p><strong>Uses</strong></p></td> </tr> <tr> <td valign="top"><p>Just-in-Time Inventory (JIT)</p></td> <td valign="top"><p>Aims to increase inventory efficiency while decreasing waste by receiving goods only when they are needed in the process</p></td> <td valign="top"><p>Reduction in waste, improved efficiency, greater productivity, smooth production flow, lower costs</p></td> <td valign="top"><p>Supply chain disruptions and order issues will impede the business; overreliance on forecasts; supplier dependence to deliver on time</p></td> <td valign="top"><p>Items that expire, manufacturing, etc.</p></td> </tr> <tr> <td valign="top"><p>Economic Order Quantity (EOQ)</p></td> <td valign="top"><p>Determines what the optimal order quantity needs to be to minimize total inventory costs including holding costs and ordering costs</p></td> <td valign="top"><p>Cash flow tool, can identify the reorder point, encourages volume orders vs. many small orders</p></td> <td valign="top"><p>Assumes steady demand, ignores seasonal or economic fluctuations</p></td> <td valign="top"><p>Stable and consistent situations</p></td> </tr> <tr> <td valign="top"><p>Materials Requirement Planning (MRP)</p></td> <td valign="top"><p>Uses detailed sales forecasts to order materials needed to produce finished items</p></td> <td valign="top"><p>Improved inventory control with optimized scheduling, cost reductions, increased efficiencies</p></td> <td valign="top"><p>Relies heavily on data and accurate forecasts, rigid planning with high complexity</p></td> <td valign="top"><p>Manufacturing goods</p></td> </tr> <tr> <td valign="top"><p>First-in-First-Out (FIFO)</p></td> <td valign="top"><p>Accounting principle that assumes oldest inventory is sold first and remaining inventory consists of newest product</p></td> <td valign="top"><p>Minimize loss due to expiry dates, easy to implement and difficult to manipulate or embellish company financials, best reflects current value of inventory</p></td> <td valign="top"><p>Can overstate profits, inventory may not be truly reflected in innovative industries where product can become obsolete due to new technology, trends, and innovation</p></td> <td valign="top"><p>Perishable goods</p></td> </tr> <tr> <td valign="top"><p>Last-in-First-Out (LIFO)</p></td> <td valign="top"><p>Accounting principle that assumes newest inventory is sold first and remaining inventory consists of oldest product</p></td> <td valign="top"><p>Can lower taxable income that leads to higher cash flow, important when expenses are rising, </p></td> <td valign="top"><p>Ending inventory value may be understated, banned under international financial reporting standards as it minimizes taxable income</p></td> <td valign="top"><p>Companies that maintain large and costly inventories</p></td> </tr> <tr> <td valign="top"><p>Days Sales of Inventory (DSI)</p></td> <td valign="top"><p>Average time in days that it takes a company to turn its inventory. A financial ratio that indicates how many days current inventory will last before being replenished</p></td> <td valign="top"><p>Shows how effectively inventory is being managed, high DSI can indicate a problem with inventory and trigger a remedial action</p></td> <td valign="top"><p>Lacks context if used as a standalone metric, does not consider seasonal fluctuations</p></td> <td valign="top"><p>All retailers as an effective inventory management metric</p></td> </tr> <tr> <td valign="top"><p>Safety Stock</p></td> <td valign="top"><p>Safety stock is inventory that is kept on hand to cover unexpected demand or supply chain disruptions</p></td> <td valign="top"><p>Safeguards against lost sales due to supplier disruptions, inaccurate forecasts, and/or market volatility</p></td> <td valign="top"><p>Excess inventory increasing costs</p></td> <td valign="top"><p>Good for unpredictable demand</p></td> </tr> <tr> <td valign="top"><p>ABC Analysis</p></td> <td valign="top"><p>Grading that group's inventory into three categories (A, B & C) based on the level of importance of the inventory </p></td> <td valign="top"><p>Optimized inventory, improved forecasting, better pricing on growth product, improved stock turnover rate, reduced costs</p></td> <td valign="top"><p>Ignores seasonal fluctuations, high-level view on inventory grouped together in B & C, arbitrary categorization, high resource consumption</p></td> <td valign="top"><p>Good for large organizations</p></td> </tr> </tbody> </table> <p>Sources: Issues Up Solutions, 2024; Investopedia, 2024.<br> <em>*A representation of principles, data, and value outcomes; not an exhaustive list </em></p> </section> <section> <h2>Leverage AI-driven inventory management principles to achieve value outcomes</h2> <table width="900" border="1"> <tbody> <tr> <th><p>Principles</p></th> <th><p>Solve for</p></th> <th><p>AI Opportunities</p></th> <th><p>Key Data Points </p></th> <th><p>Reduced Costs, Waste, and Spoilage</p></th> <th><p>Improved Profit Margins</p></th> <th><p>Increased Operational Efficiency</p></th> <th><p>Faster Response to Market Changes</p></th> <th><p>Improved Supplier Relationships</p></th> <th><p>Enhanced Customer Satisfaction</p></th> </tr> <tr> <td><p>Just-in-Time Inventory (JIT)</p></td> <td><p>Over or under stocking; inefficient coordination in the supply chain</p></td> <td><p>Assist in optimizing deliveries and supply chain coordination through real-time AI-powered algorithms that generate demand forecasts and analyze inventory in real time</p></td> <td><p>Sales history, market trends, lead time, supplier reliability, inventory (from IoT, RFID etc.)</p></td> <td><p>✔</p></td> <td><p>✔</p></td> <td><p>✔</p></td> <td><p>✔</p></td> <td><p>✔</p></td> <td><p>✔</p></td> </tr> <tr> <td><p>Economic Order Quantity (EOQ)</p></td> <td><p>Optimize order quantities; minimize carrying costs</p></td> <td><p>Dynamically adjust order quantities based on real-time data analysis</p></td> <td><p>Sales & order history, lead times, holding cost per unit</p></td> <td><p>✔</p></td> <td><p>✔</p></td> <td><p>✔</p></td> <td></td> <td><p>✔</p></td> <td></td> </tr> <tr> <td><p>Materials Requirement Planning (MRP)</p></td> <td><p>Align material purchases and production needs</p></td> <td><p>Enhance material planning by predicting demand and optimizing orders</p></td> <td><p>Sales history, production schedule, bill of materials, supplier performance</p></td> <td><p>✔</p></td> <td><p>✔</p></td> <td><p>✔</p></td> <td><p>✔</p></td> <td><p>✔</p></td> <td><p>✔</p></td> </tr> <tr> <td><p>First-in-First-Out (FIFO)</p></td> <td><p>Ensure oldest stock is sold first</p></td> <td><p>Automate stock rotation and ensure accurate tracking of product age</p></td> <td><p>Sales velocity, product shelf life, expiry dates</p></td> <td><p>✔</p></td> <td><p>✔</p></td> <td><p>✔</p></td> <td></td> <td></td> <td><p>✔</p></td> </tr> <tr> <td><p>Last-in-First-Out (LIFO)</p></td> <td><p>Ensure newest stock is sold first</p></td> <td><p>Automate stock rotation and track inventory for more accurate reporting</p></td> <td><p>Purchase date, sales velocity, cost of goods</p></td> <td><p>✔</p></td> <td><p>✔</p></td> <td></td> <td></td> <td></td> <td></td> </tr> <tr> <td><p>Days Sales of Inventory (DSI)</p></td> <td><p>Track inventory turn rate and stock efficiency</p></td> <td><p>Provide real-time monitoring and actionable insights into increasing turnover rates</p></td> <td><p>Sales history, inventory position, order frequency, market trends</p></td> <td><p>✔</p></td> <td><p>✔</p></td> <td></td> <td><p>✔</p></td> <td></td> <td></td> </tr> <tr> <td><p>Safety Stock</p></td> <td><p>Calculate and maintain optimal safety stock</p></td> <td><p>Predict demand and possible disruptions to optimize safety stock levels</p></td> <td><p>Sales history, inventory position, supplier reliability, demand variability</p></td> <td><p>✔</p></td> <td><p>✔</p></td> <td><p>✔</p></td> <td><p>✔</p></td> <td><p>✔</p></td> <td><p>✔</p></td> </tr> <tr> <td><p>ABC Analysis</p></td> <td><p>Classify inventory items in the most meaningful way</p></td> <td><p>Automate categorization and continuously update stock categories</p></td> <td><p>Sales history, turnover rates, profit margins, inventory position</p></td> <td><p>✔</p></td> <td><p>✔</p></td> <td><p>✔</p></td> <td><p>✔</p></td> <td><p>✔</p></td> <td><p>✔</p></td> </tr> </tbody> </table> </section> <section> <h2>Consider the risks of AI</h2> <h3>There are more than the usual number of risks with AI technology.</h3> <p><img src="https://cdn1-public.infotech.com/blueprints/Build-Your-AI-Strategy-for-Retail-Inventory-Management-Storyboard/ai-risks-iceberg.png" loading="lazy" width="800" height="346" alt="An image of an iceberg, with the following AI risks: Trust, Continuous Improvement, Bias, Accountability, Technology, Privacy and security."></p> </section> <section> <h2>Building your AI strategy use case library for inventory management</h2> <p><strong>What Is Known</strong></p> <ul> <li>AI has the power to transform how inventory is managed.</li> <li>Leveraging AI can reduce excess inventory and optimize stock.</li> </ul> <p><strong>Actions To Take</strong></p> <ol start="1" type="1"> <li>Identify areas within the inventory management process where AI can provide the most impact – Step 4 in <em>Build Your AI Strategy Roadmap.</em></li> <li>Systemically build your AI use case library for inventory management based on the value proposition and feasibility of each use case – Step 5 in <em>Build Your AI Strategy Roadmap.</em></li> <li>Prioritize and build a structured path toward adopting AI in inventory management – Step 6 in <em>Build Your AI Strategy Roadmap.</em></li> </ol> <p>"Achieving high levels of forecasting accuracy is not easy, as it depends on many factors, such as the quality and availability of data, the choice and suitability of forecasting methods, the skill and experience of forecasters, and the alignment and communication of forecasts across the organization."</p> <p>Source: FasterCapital, 2024</p> </section> <section><img src="https://cdn1-public.infotech.com/blueprints/Build-Your-AI-Strategy-for-Retail-Inventory-Management-Storyboard/build-your-ai-strategy-roadmap.png" loading="lazy" width="950" height="528" alt="Build your AI Strategy Roadmap, steps 1-7."> </section> <section> <h2>Info-Tech's approach and team can help, irrespective of where you are in your digital journey</h2> <p><img src="https://cdn1-public.infotech.com/blueprints/Build-Your-AI-Strategy-for-Retail-Inventory-Management-Storyboard/info-tech's-approach.png" loading="lazy" width="1146" height="568" alt="An image of a table outlining Info-Tech's Approach to the Digital Journey"></p> </section> <section> <h2>How to use this report</h2> <p>Visit Info-Tech's<em> <u><a href="https://www.infotech.com/research/ss/build-your-ai-strategy-roadmap">Build Your AI Strategy Roadmap </a></u></em>blueprint for full activity details</p> <p>Use this map to determine where to use this research material.</p> <p>This report is designed to complement Info-Tech's comprehensive Build Your AI Strategy Roadmap blueprint and associated activities. It uses research-based data for "ACME Corp Data" to demonstrate AI use case opportunities for use in a holistic AI strategy and roadmap. Once you have completed the activities within this report, return to the core research to progress through the remaining phases of the broader strategy. </p> <p>Realize all teams are unique and you may feel that some sample information may not be relevant to or represent your organization well due to the different type of products and services you are engaged in, geographic area you're located in, etc. We recommend that you adjust and customize the template as needed to be organization-specific and to create the most valuable AI strategy for your organization. </p> <p>You will use this report as a research-based accelerant input as you work through phases 2 and 3 and activities 2.1 and 3.1 of <em>Build Your AI Strategy Roadmap</em> blueprint, specifically:</p> <table width="578" border="1"> <tbody> <tr> <th colspan="2" scope="col"><p>AI strategy roadmap activities</p></th> </tr> <tr> <td width="284"><h3> Phase 2</h3></td> <td width="278"><h3> Phase 3</h3></td> </tr> <tr> <td><p><strong>Identify AI Use Cases</strong></p></td> <td><p><strong>Prioritize AI Use Cases</strong></p></td> </tr> <tr> <td><p>Activity 2.1 Map your candidate AI use cases</p></td> <td><p>Activity 3.1 Prioritize candidate AI use cases</p></td> </tr> </tbody> </table> </section> <section> <h2>Measure the value of this document</h2> <h3><strong>Document your objective</strong></h3> <p>Highlight best-in-class use cases to spur the initiative-planning and ideation process.</p> <h3><strong>Measure your success against that objective</strong></h3> <p>There are multiple qualitative and quantitative, direct and indirect metrics by which you can measure the progress of your initiative pipeline's development. Some examples are:</p> <ul> <li>Increased initiative pipeline value </li> <li>Number of capabilities impacted by initiative pipeline</li> <li>Enhanced understanding of the initiatives' impact aligned to the organization's capability map</li> <li>Better understanding of which sources of value are being addressed or under-addressed in the organization's initiative pipeline</li> </ul> <p>See <em><a href="https://www.infotech.com/research/ss/establish-your-digital-transformation-governance">Establish Your Digital Transformation Governance</a></em>in the <a href="https://www.infotech.com/digital-transformation-center">Digital Transformation Center</a> for more details</p> </section> <section> <h2>AI in retail inventory management aims to produce measurable results</h2> <table width="900" border="1"> <tbody> <tr> <th><p>Operational Value Outcomes</p></th> <th><p>Metrics</p></th> <th><p>Impacts</p></th> <th><p>Measures</p></th> </tr> <tr> <th><p>Reduced Costs, Waste, and Spoilage</p></th> <td><p>Inventory carry costs, shrink rates, spoilage percentages</p></td> <td><p>Lower storage costs, reduced, expired, or unsold inventory</p></td> <td><p>Shrink rates and carrying costs</p></td> </tr> <tr> <th><p>Improved Profit Margins</p></th> <td><p>Order cycle time, inventory turns, warehouse processing time</p></td> <td><p>Streamline operations, fewer errors, faster replenishment</p></td> <td><p>Turnover ratios, lead time</p></td> </tr> <tr> <th><p>Increased Operational Efficiency </p></th> <td><p>Gross margin, profit per SKU, operating cost percentages</p></td> <td><p>Higher profitability, reduced markdowns, optimized pricing</p></td> <td><p>Gross margin percentages</p></td> </tr> <tr> <th><p>Faster Response to Market Changes</p></th> <td><p>Time to replenish, stock availability, inventory turns</p></td> <td><p>Ability to adapt to market shifts and demand changes</p></td> <td><p>Allocation and replenishment response time, stock availability</p></td> </tr> <tr> <th><p>Improved Supplier Relationships</p></th> <td><p>Supplier lead times, on-time delivery rate, order accuracy</p></td> <td><p>Stronger supplier relationships, improved trust</p></td> <td><p>On-time delivery metrics, supplier satisfaction scores</p></td> </tr> <tr> <th><p>Enhanced Customer Satisfaction</p></th> <td><p>Customer satisfaction scores (CSAT), net promoter score (NPS), order fulfilment rates</p></td> <td><p>Increased customer loyalty, customer retention through repeat purchases</p></td> <td><p>CSAT, NPS, reduced returns</p></td> </tr> </tbody> </table> </section> <section> <h2>AI Use Case Library Methodology</h2> <h3>SECTION 1</h3> </section> <section> <h2>AI in Inventory Management Value Chain Framework</h2> <p>Generate value and deliver results by focusing on activities to create and capture value, emphasizing end-to-end processes.</p> <h3>VALUE CHAIN DEVELOPMENT</h3> <p><img src="https://cdn1-public.infotech.com/blueprints/Build-Your-AI-Strategy-for-Retail-Inventory-Management-Storyboard/value-chain-development.png" loading="lazy" width="800" height="334" alt="An image of the Inventory Management Value Chain Framework"></p> <h3>FOCUS ON PRIMARY AND SECONDARY ACTIVITIES TO DRIVE VALUE IMPROVEMENT</h3> </section> <section> <h2>What is an AI use case?</h2> <h3>An AI use case is a technology, or combination of technologies, applied to a specific capability (e.g. job to be done) within a given industry or function to create value.</h3> <h3>Use Case</h3> <p><strong>Industry or Function</strong><br> The relevant industry or function (many use cases will apply across multiple industries or functions).</p> <p><strong>Capabilities<br> </strong>The activities, or jobs to be done, that your organization performs to ultimately deliver a product <br> or service.</p> <p><strong>Technology<br> </strong>The base technology that enables value-creating performance gains.</p> </section> <section> <h2>The AI use case library</h2> <h3>What is it?</h3> <p>A use case represents a technology or combination of technologies applied to a capability within a given industry or function that drives value. The AI use case library is a non-exhaustive list of Gen AI/AI/ML use cases that can be organized by industry/function, capability, or technology. The organizing principle in this document is by industry/function.</p> <h3>Why is it important?</h3> <p>In the context of a digital transformation, the Gen AI/AI/ML use case library:</p> <ul> <li>Identifies potential sources of value to analyze in a top-down opportunity assessment. </li> <li>Jumpstarts the idea generation process during the initiative development phase. Use cases are the foundational building blocks of the initiatives that ultimately deliver value to the business. </li> </ul> <h3>Use cases are the strategic building blocks of business reference architecture capabilities that ultimately deliver value to the organization. </h3> <p><strong>Use Case</strong></p> <ul> <li>Industry or Function</li> <li>Capabilities</li> <li>Technology</li> </ul> </section> <section> <h2>AI use case library</h2> <h3>Leverage best-in-class capabilities-based use cases to build strong implementation roadmaps and maximize value creation.</h3> <p><img src="https://cdn1-public.infotech.com/blueprints/Build-Your-AI-Strategy-for-Retail-Inventory-Management-Storyboard/ai-use-case-library.png" loading="lazy" width="900" height="391" alt="An image of the AI use case library"></p> </section> <section> <h2>Leverage your industry's capability maps to identify candidate use case opportunities</h2> <h3>Retail Industry Capabilities Reference Model</h3> <p><img src="https://cdn1-public.infotech.com/blueprints/Build-Your-AI-Strategy-for-Retail-Inventory-Management-Storyboard/retail-industry-capabilities-reference-model.png" loading="lazy" width="751" height="467" alt="Retail Industry Capabilities Reference Model"></p> <h3>Business capability map defined:</h3> <p>In business architecture, the primary view of an organization is known as a business capability map. </p> <p>A business capability defines what a business does to enable value creation, rather than how. Business capabilities:</p> <ul> <li>Represent stable business functions.</li> <li>Are unique and independent of each other. </li> <li>Typically, will have a defined business outcome.</li> </ul> <p>A business capability map provides details that help the business architecture practitioner direct attention to a specific area of the business for further assessment.</p> </section> <section> <h2>Retail and Wholesale Capabilities Tree</h2> <p><strong>Value Streams</strong></p> <p>Core components of an organization's value chain or support structure </p> <p><strong>Level 1: Capabilities</strong></p> <p>The top-level activities that your organization performs to ultimately deliver a product/service</p> <p><strong>Level 2: Sub-Capabilities</strong></p> <p>The sub-activities, or jobs to be done, that are performed within an overarching capability</p> <p>Download the <u><a href="https://www.infotech.com/research/ss/retail-industry-business-reference-architecture"><em>Retail Industry Business Reference Architecture </em></a></u><em>& <u><a href="https://www.infotech.com/research/ss/wholesale-industry-business-reference-architecture">Wholesale</a> Industry Business Reference Architecture Templates</u></em></p> <p><img src="https://cdn1-public.infotech.com/blueprints/Build-Your-AI-Strategy-for-Retail-Inventory-Management-Storyboard/retail-and-wholesale-capabilities-tree.png" loading="lazy" width="600" height="538" alt="Retail and Wholesale Capabilities Tree"></p> <p>Use cases apply to a specific Level 1 or Level 2 capability within the industry value stream.</p> </section> <section> <h2>AI uses case library for inventory management </h2> <p>This use case library will focus on five Level-1 capabilities in the Retail Industry Capabilities Reference model. The capabilities chosen fall under the following three value streams and include: Demand Forecasting, Procurement Management, Supply Chain Management, Allocation & Replenishment, and Store Management. </p> <p>While working through this exercise, you may choose to include additional capabilities off which to build out your own AI use case library for inventory management and Info-Tech can further assist on an advisory call.</p> <p><img src="https://cdn1-public.infotech.com/blueprints/Build-Your-AI-Strategy-for-Retail-Inventory-Management-Storyboard/retail-industry-capabilities-reference-model1.png" loading="lazy" width="702" height="277" alt="Snapshot of the broader Retail Industry Capabilities Reference model for the purpose of this use case library."></p> <p>Snapshot of the broader Retail Industry Capabilities Reference model for the purpose of this use case library.</p> </section> <section> <h2>Enhance your value chain with AI in inventory management</h2> <h3>Value Chain Examples</h3> <p><img src="https://cdn1-public.infotech.com/blueprints/Build-Your-AI-Strategy-for-Retail-Inventory-Management-Storyboard/example-value-chains.png" loading="lazy" width="900" height="335" alt="two example value chains, for reducing costs, waste, spoilage, and improved supplier relations."></p> <p><em>Example value chains; not an exhaustive representation</em></p> </section> <section> <h2>Leading AI techniques used in retail inventory management</h2> <h3>The use of AI methods in retail inventory management leverages advanced technologies to optimize stock, improve operational efficiencies, and enhance the overall customer shopping experience. The following is a list of the AI techniques most often used.</h3> <table width="900" border="1"> <tbody> <tr> <td></td> <th><p><strong>AI Techniques*</strong></p></th> <th><p>Opportunities for Retail</p></th> </tr> <tr> <td><p><strong>1</strong></p></td> <td><p><strong>Machine Learning</strong></p></td> <td><ul> <li>Machine learning, predicting future demand using historical sales, seasonality, trends, competitor data</li> <li>Adjust inventory level dynamically based on changing demand, supply chain constraints, etc.</li> </ul> </td> </tr> <tr> <td><p><strong>2</strong></p></td> <td><p><strong>Supervised Learning</strong></p></td> <td><ul> <li>Train models on customer past purchases and behaviors</li> <li>Allows system to predict and classify new data for segmenting customers and product</li> </ul> </td> </tr> <tr> <td><p><strong>3</strong></p></td> <td><p><strong>Unsupervised Learning</strong></p></td> <td><ul> <li>Identify outliers and discrepancies such as theft, loss, data entry errors</li> <li>Detect unusual patterns in stock movement</li> <li>Prevent stockouts or overstocking</li> </ul> </td> </tr> <tr> <td><p><strong>4</strong></p></td> <td><p><strong>Computer Vision</strong></p></td> <td><ul> <li>Shelf monitoring – warehouse, in-store, backroom</li> <li>Automate inventory auditing – AI powered cameras to scan shelves/compare counts to on-hand inventory</li> </ul> </td> </tr> <tr> <td><p><strong>5</strong></p></td> <td><p><strong>Automation and Robotics</strong></p></td> <td><ul> <li>Automate repetitive inventory management task such as: ordering, allocation, replenishment, pick/pack/ship, using AI bots</li> </ul></td> </tr> <tr> <td><p><strong>6</strong></p></td> <td><p><strong>Predictive Stock Replenishment</strong></p></td> <td><ul> <li>Automate product ordering, allocation, and replenishment</li> <li>Improve inventory efficiency through alerts</li> </ul> </td> </tr> <tr> <td><p><strong>7</strong></p></td> <td><p><strong>Natural Language Processing</strong></p></td> <td><ul> <li>Use Gen AI through chatbots for employee and customer queries</li> <li>Extract insights from unstructured data such as text (customer reviews), images (trending product) to predict demand</li> </ul> </td> </tr> <tr> <td><p><strong>8</strong></p></td> <td><p><strong>Simulations & Scenario Planning</strong></p></td> <td><ul> <li>Create a digital twin to simulate scenarios and test strategies</li> <li>Predict impact of unknown factors on inventory and have contingency plans</li> </ul> </td> </tr> </tbody> </table> <p><em>*Not an exhaustive list</em></p> </section> <section> <h2>2.1 Map your candidate AI use cases (Part 1)</h2> <h3>1-3 hours</h3> <ol> <li>Gather the AI strategy creation team and revisit your strategy context inputs, specifically your organization's business goals, business initiatives, value streams, and business capability map. </li> <li>Review the following top AI opportunity use cases for inventory management and discuss possible AI use cases your organization can leverage to bring value. Try not to prioritize or score each candidate use case as that will be done in a subsequent activity, rather, highlight, circle, whiteboard, sticky note, or use an online collaboration tool to keep track of your shortlisted and new use case ideas.</li> </ol> <p>Download the <a href="https://www.infotech.com/research/ai-strategy-and-discovery-presentation-template"><em>AI Strategy and Discovery Presentation Template</em></a></p> <table width="509" border="1"> <tbody> <tr> <th width="213"><p>Input</p></th> <th width="280"><p>Output</p></th> </tr> <tr> <td valign="top"><ol> <li>Business goals</li> <li>Business initiatives</li> <li>Business capability map</li> <li>AI use cases</li> </ol></td> <td valign="top"><ol> <li>Business aligned AI use cases list</li> </ol></td> </tr> <tr> <th valign="top"><p>Materials</p></th> <th valign="top"><p>Participants</p></th> </tr> <tr> <td valign="top"><ol> <li>Collaboration/brainstorming tool (whiteboard, flip chart, digital equivalent) </li> <li><em>AI Strategy and Discovery Presentation Template</em></li> </ol></td> <td valign="top"><ol> <li>AI initiative lead</li> <li>CIO</li> <li>Other IT leadership</li> <li>Senior business executives and managers accountable for AI initiatives</li> </ol></td> </tr> </tbody> </table> </section> <section> <h2>Top AI Opportunities in Inventory Management</h2> <h3>SECTION 2</h3> </section> <section> <h2>Key retail business capabilities used to highlight significant use cases</h2> <table width="900" border="1"> <tbody> <tr> <td colspan="2" valign="top"><h3>Retail capabilities impacting retail inventory management</h3></td> </tr> <tr> <td colspan="2"><p>The goal of identifying effective use cases is to set the organization up for success when implementing an AI strategy for retail inventory management and ranking the impact to the overall inventory performance. The following retail capabilities are key to identifying relevant use cases for AI-driven inventory management in the retail industry.</p></td> </tr> <tr> <td><p><strong>Demand Forecasting</strong></p></td> <td valign="top"><p>The process of predicting future customer demand; it involves analyzing multiple data points such as historical sales, market trends, seasonal patterns, and external factors to estimate the volume of needed products and/or services. Demand forecasting directly impacts inventory management by optimizing inventory levels by reducing stockouts and excess inventory.</p></td> </tr> <tr> <td><p><strong>Procurement Management</strong></p></td> <td valign="top"><p>Focuses on the acquisition of goods, services, and resources needed to effectively operate the business. It involves supplier selection, contract negotiation, contract management, and purchasing. Establishes reliable vendors and sourcing on favorable terms, enables the business to acquire and receive the right product at the right time.</p></td> </tr> <tr> <td><p><strong>Supply Chain Management (SCM)</strong></p></td> <td valign="top"><p>Oversees the flow of goods throughout the supply chain from suppliers to the point of sale and involves coordination of multiple touch points. Success is achieved through efficient processes that ensure timely and accurate product delivery. Inventory management is a component of this capability where overall SCM improves visibility and control of inventory.</p></td> </tr> <tr> <td><p><strong>Allocation & Replenishment</strong></p></td> <td valign="top"><p>Distributing product from one or more warehouse locations directly to consumer and/or other physical locations such as stores and/or wholesale customers. This capability has significant impact on inventory management as proper distribution increasing inventory turns and balanced inventory across all channels.</p></td> </tr> <tr> <td><p>Store Management</p></td> <td valign="top"><p>Encompasses all activities that relate to operating a physical store, including daily operations, staff management, merchandising, and customer service. In relation to inventory management, effective store management is crucial through increasing inventory turns and optimizing store layouts, stock available for purchase, returns, and shrink management.</p></td> </tr> </tbody> </table> </section> <section> <h2>AI-driven inventory management: Enhances demand forecasting</h2> <table width="900" border="1"> <tbody> <tr> <th scope="row"> </th> <th colspan="6"><h3>Sources of Value</h3></th> </tr> <tr> <td><p><strong>Value Stream: Purchase Product</strong></p></td> <td><p><strong>Operational Efficiency</strong></p></td> <td><p><strong>Customer Experience</strong></p></td> <td><p><strong>Business Growth</strong></p></td> <td><p><strong>Employee Experience</strong></p></td> <td><p><strong>Risk and</strong><br> <strong>Resiliency</strong></p></td> <td><p><strong>ESG</strong></p></td> </tr> <tr> <td><p>Capability: Demand Forecasting</p></td> <td valign="top"></td> <td valign="top"></td> <td valign="top"></td> <td valign="top"></td> <td valign="top"></td> <td valign="top"></td> </tr> <tr> <td><p><strong>Demand & Inventory Forecasting: </strong>Utilize AI to automatically analyze historical sales data, seasonal trends, peak selling periods (holidays, back-to-school, etc.) and external factors (weather patterns, etc.) to accurately predict future demand.</p></td> <td><p>✔</p></td> <td></td> <td><p>✔</p></td> <td><p>✔</p></td> <td></td> <td><p>✔</p></td> </tr> <tr> <td><p><strong>Reduce Stockouts: </strong>Through AI-powered data analysis, predict potential stockouts by analyzing sales trends, inventory turn rates and product lead times, enabling automatic reorder of products based on an AI-derived demand forecast.</p></td> <td><p>✔</p></td> <td><p>✔</p></td> <td><p>✔</p></td> <td><p>✔</p></td> <td></td> <td></td> </tr> <tr> <td><p><strong>Inventory Optimization: </strong>Use AI to analyze factors such as sales velocity, carrying costs, lead times, and service level requirement. AI recommends an optimal inventory level by location, reducing excess inventory in any given location, improving sales potential.</p></td> <td><p>✔</p></td> <td><p>✔</p></td> <td></td> <td></td> <td></td> <td><p>✔</p></td> </tr> <tr> <td><p><strong>Overstock Reduction: </strong>AI models identify slow-moving inventory, recommend optimal order quantities and identifies price and promotional strategies to clear excess stock. This optimizes in-store and warehouse space, freeing up cashflow for ordering product.</p></td> <td><p>✔</p></td> <td><p>✔</p></td> <td><p>✔</p></td> <td><p>✔</p></td> <td></td> <td><p>✔</p></td> </tr> <tr> <td><p><strong>Perishable Goods Management: </strong>Use AI to optimize perishable-goods inventory by predicting demand and recommending price and promotional campaigns on excess, expiring product, reducing spoilage.</p></td> <td><p>✔</p></td> <td><p>✔</p></td> <td><p>✔</p></td> <td><p>✔</p></td> <td></td> <td><p>✔</p></td> </tr> </tbody> </table> <p>Note: Evaluation metrics are close approximations and for illustrative purposes only. Sources of value may vary in your organization, sector, or jurisdiction. </p> </section> <section> <h2>AI-driven inventory management: Improves procurement management</h2> <table width="900" border="1"> <tbody> <tr> <th scope="row"> </th> <th colspan="6"><h3>Sources of Value</h3></th> </tr> <tr> <td><p><strong>Value Stream: Purchase Product</strong></p></td> <td><p><strong>Operational Efficiency</strong></p></td> <td><p><strong>Customer Experience</strong></p></td> <td><p><strong>Business Growth</strong></p></td> <td><p><strong>Employee Experience</strong></p></td> <td><p><strong>Risk and</strong><br> <strong>Resiliency</strong></p></td> <td><p><strong>ESG</strong></p></td> </tr> <tr> <td><p>Capability: Procurement Management</p></td> <td valign="top"></td> <td valign="top"></td> <td valign="top"></td> <td valign="top"></td> <td valign="top"></td> <td valign="top"></td> </tr> <tr> <td><p><strong>Automate Reorder: </strong>AI monitors real-time inventory levels and automatically generates purchase orders when stock falls below a predefined threshold, helping to maintain optimal inventory on hand and reducing manual workload.</p></td> <td><p>✔</p></td> <td></td> <td><p>✔</p></td> <td><p>✔</p></td> <td></td> <td></td> </tr> <tr> <td><p><strong>Supplier Selection and Evaluation: </strong>AI-Driven analytics can assess suppliers by analyzing data such as pricing, quality, lead times, compliance records, etc., and suggest best-fit suppliers. This can ensure more favorable terms and better quality, lowering costs by providing efficient inventory management.</p></td> <td><p>✔</p></td> <td></td> <td><p>✔</p></td> <td><p>✔</p></td> <td><p>✔</p></td> <td><p>✔</p></td> </tr> <tr> <td><p><strong>Cost Optimization and Contract Negotiation: </strong>AI evaluates past purchasing patterns, market trends, pricing, competitors and currency fluctuations, and provides recommendations that can assist in negotiating volume discounts and more favorable terms.</p></td> <td><p>✔</p></td> <td></td> <td><p>✔</p></td> <td><p>✔</p></td> <td><p>✔</p></td> <td><p>✔</p></td> </tr> <tr> <td><p><strong>Quality Control: </strong>AI tools analyze vast amounts of data from audits, inspection reports, and regulation updates, providing early detection on problem areas, allowing procurement teams to quickly address issues that affect quality and maintain optimal inventory levels.</p></td> <td><p>✔</p></td> <td></td> <td><p>✔</p></td> <td><p>✔</p></td> <td><p>✔</p></td> <td><p>✔</p></td> </tr> <tr> <td><p><strong>Risk Mitigation: </strong>AI can predict supply chain disruptions, providing early warnings that allow procurement teams to adapt and shift to alternate suppliers with low impact to the business while minimizing inventory disruptions.</p></td> <td><p>✔</p></td> <td></td> <td><p>✔</p></td> <td><p>✔</p></td> <td><p>✔</p></td> <td><p>✔</p></td> </tr> </tbody> </table> <p>Note: Evaluation metrics are close approximations and for illustrative purposes only. Sources of value may vary in your organization, sector, or jurisdiction. </p> </section> <section> <h2>AI-driven inventory management: Optimizes supply chain management</h2> <table width="900" border="1"> <tbody> <tr> <th scope="row"> </th> <th colspan="6"><h3>Sources of Value</h3></th> </tr> <tr> <td><p><strong>Value Stream: Distribute Product</strong></p></td> <td><p><strong>Operational Efficiency</strong></p></td> <td><p><strong>Customer Experience</strong></p></td> <td><p><strong>Business Growth</strong></p></td> <td><p><strong>Employee Experience</strong></p></td> <td><p><strong>Risk and</strong><br> <strong>Resiliency</strong></p></td> <td><p><strong>ESG</strong></p></td> </tr> <tr> <td><p>Capability: Supply Chain Management</p></td> <td valign="top"></td> <td valign="top"></td> <td valign="top"></td> <td valign="top"></td> <td valign="top"></td> <td valign="top"></td> </tr> <tr> <td><p><strong>Supply Chain Optimization: </strong>Using predictive analytics that consume historical data, supplier data, market trend, economic indicators, etc., optimize the end-to-end supply chain and provide proactive contingency plans in the event of future disruptions.</p></td> <td><p>✔</p></td> <td></td> <td><p>✔</p></td> <td></td> <td><p>✔</p></td> <td><p>✔</p></td> </tr> <tr> <td><p><strong>Route and Logistics Optimization: </strong>AI algorithms adjust shipping routes, transportation, and delivery times based on ideal logistic strategies – reducing logistics costs and improving reliability and increasing product replenishment timing.</p></td> <td><p>✔</p></td> <td></td> <td><p>✔</p></td> <td></td> <td><p>✔</p></td> <td><p>✔</p></td> </tr> <tr> <td><p><strong>Inventory Auditing: </strong>Implement AI-enabled tools like computer vision, RFID scanning to perform automated inventory counts in warehouse and in-store, providing real-time volume discrepancies, reducing errors that are associated with manual audits.</p></td> <td><p>✔</p></td> <td></td> <td></td> <td><p>✔</p></td> <td><p>✔</p></td> <td><p>✔</p></td> </tr> <tr> <td><p><strong>Fraud Detection in Inventory: </strong>Utilize AI-enabled tools that detect anomalies and flag transactions, movements, and other suspicious activities to be further investigated, leading to a reduction in shrinkage and lost inventory.</p></td> <td><p>✔</p></td> <td><p>✔</p></td> <td><p>✔</p></td> <td><p>✔</p></td> <td><p>✔</p></td> <td><p>✔</p></td> </tr> <tr> <td><p><strong>Real-Time Visibility and Alerts:</strong> Combining AI with real-time IoT data, provide accurate location of all inventory including shipments and owned inventory. AI alerts notify of potential issues including delays or spoilage in shipments and low stock positions within stores giving businesses time to mitigate damages. </p></td> <td><p>✔</p></td> <td></td> <td></td> <td><p>✔</p></td> <td><p>✔</p></td> <td><p>✔</p></td> </tr> </tbody> </table> <p>Note: Evaluation metrics are close approximations and for illustrative purposes only. Sources of value may vary in your organization, sector, or jurisdiction. </p> </section> <section> <h2>AI-driven inventory management: Advances allocation & replenishment</h2> <table width="900" border="1"> <tbody> <tr> <th scope="row"> </th> <th colspan="6"><h3>Sources of Value</h3></th> </tr> <tr> <td><p><strong>Value Stream: Distribute Product</strong></p></td> <td><p><strong>Operational Efficiency</strong></p></td> <td><p><strong>Customer Experience</strong></p></td> <td><p><strong>Business Growth</strong></p></td> <td><p><strong>Employee Experience</strong></p></td> <td><p><strong>Risk and</strong><br> <strong>Resiliency</strong></p></td> <td><p><strong>ESG</strong></p></td> </tr> <tr> <td><p>Capability: Allocation & Replenishment</p></td> <td valign="top"></td> <td valign="top"></td> <td valign="top"></td> <td valign="top"></td> <td valign="top"></td> <td valign="top"></td> </tr> <tr> <td><p><strong>Automate Allocation & Replenishment: </strong>AI-driven allocation and replenishment adapts in real time when customer buying patterns shift and unexpected events occur. It can recognize abnormal spikes and/or drops in demand by location and adjust delivery of products by store to the SKU level.</p></td> <td><p>✔</p></td> <td><p>✔</p></td> <td><p>✔</p></td> <td></td> <td></td> <td><p>✔</p></td> </tr> <tr> <td><p><strong>Group/Identify Like Product: </strong>Use AI to identify and group like products together when determining the allocation and replenishment volumes by location. This helps in ensuring that matching sets are available in-store for purchase and allocated and replenished to optimize sales potential.</p></td> <td><p>✔</p></td> <td><p>✔</p></td> <td><p>✔</p></td> <td><p>✔</p></td> <td></td> <td></td> </tr> <tr> <td><p><strong>Order Fulfilment Optimization: </strong>Use AI to improve order processing by optimizing pick-locations within the warehouse, grouping high-volume product that ships together in proximity and batching orders, speeding up delivery time and improving inventory management.</p></td> <td><p>✔</p></td> <td><p>✔</p></td> <td><p>✔</p></td> <td></td> <td></td> <td><p>✔</p></td> </tr> <tr> <td><p><strong>Intelligent Store-to-Store Rebalance: </strong>AI models can identify cost-effective opportunities that can be achieved by transferring product between locations, maximizing sales, reducing aging inventory by location, and freeing up key back-room and on-the-floor real-estate for better performing products.</p></td> <td><p>✔</p></td> <td><p>✔</p></td> <td><p>✔</p></td> <td><p>✔</p></td> <td></td> <td><p>✔</p></td> </tr> </tbody> </table> <p>Note: Evaluation metrics are close approximations and for illustrative purposes only. Sources of value may vary in your organization, sector, or jurisdiction. </p> </section> <section> <h2>AI-driven inventory management: Boosts store management</h2> <table width="900" border="1"> <tbody> <tr> <th scope="row"> </th> <th colspan="6"><h3>Sources of Value</h3></th> </tr> <tr> <td><p><strong>Value Stream: Sell Product</strong></p></td> <td><p><strong>Operational Efficiency</strong></p></td> <td><p><strong>Customer Experience</strong></p></td> <td><p><strong>Business Growth</strong></p></td> <td><p><strong>Employee Experience</strong></p></td> <td><p><strong>Risk and</strong><br> <strong>Resiliency</strong></p></td> <td><p><strong>ESG</strong></p></td> </tr> <tr> <td><p>Capability: Store Management</p></td> <td valign="top"></td> <td valign="top"></td> <td valign="top"></td> <td valign="top"></td> <td valign="top"></td> <td valign="top"></td> </tr> <tr> <td><p><strong>Customer Behavior Analysis: </strong>Use AI-enabled applications and tools to analyze customer buying behavior and identify preferences, allowing retailers to provide product recommendations and tailor product offerings based on the predicted customer demand.</p></td> <td><p>✔</p></td> <td><p>✔</p></td> <td><p>✔</p></td> <td><p>✔</p></td> <td></td> <td></td> </tr> <tr> <td><p><strong>Shelf Space Optimization: </strong>Employ AI to monitor and analyze customer movement within stores and identify areas where foot traffic is high/low. Optimize where product should be placed in-store for visibility and impulse buying leading to increased sales and optimized inventory in-store.</p></td> <td><p>✔</p></td> <td><p>✔</p></td> <td><p>✔</p></td> <td><p>✔</p></td> <td></td> <td></td> </tr> <tr> <td><p><strong>Chatbots for Inventory Queries: </strong>Use AI chatbots to help staff and customers in real time find inventory information including in-store, warehouse and incoming stock, which improves service levels and helps manage inventory not yet received in-store.</p></td> <td><p>✔</p></td> <td><p>✔</p></td> <td><p>✔</p></td> <td><p>✔</p></td> <td></td> <td><p>✔</p></td> </tr> <tr> <td><p><strong>In-Store Loss Prevention: </strong>Use RFID technology along with AI-powered systems to monitor in-store stock in real time, including when inventory is taken off shelf, placed in a cart and/or leaving the store without being purchased.</p></td> <td><p>✔</p></td> <td></td> <td></td> <td><p>✔</p></td> <td><p>✔</p></td> <td></td> </tr> </tbody> </table> <p>Note: Evaluation metrics are close approximations and for illustrative purposes only. Sources of value may vary in your organization, sector, or jurisdiction. </p> </section> <section> <h2>2.1 Map your candidate AI use cases (Part 2)</h2> <h3>1-3 hours</h3> <ol start="1" type="1"> <li>Gather the AI strategy creation team and, using the list of Top AI Opportunity Use Cases for Inventory Management created earlier in this activity, map these use cases based on whichever business goal they are associated with to create your business goals to AI use cases cascade visual for your AI strategy. This will help you visualize the alignment between use cases and business goals as illustrated in example 1 on the next slide.</li> <li>Next, leverage the examples in the following slides as an input to the <em>AI Strategy and Discovery Presentation Template</em> to detect possible challenges and opportunities you may run into while implementing these use cases. </li> </ol> <p>Download the <a href="https://www.infotech.com/research/ai-strategy-and-discovery-presentation-template"><em>AI Strategy and Discovery Presentation Template</em></a></p> <table width="512" border="1"> <tbody> <tr> <th width="216"><p>Input</p></th> <th width="280"><p>Output</p></th> </tr> <tr> <td valign="top"><ul> <li>Business goals</li> <li>Business initiatives</li> <li>Business capability map</li> <li>AI use cases</li> </ul></td> <td valign="top"><ul> <li>Business-aligned AI use cases list</li> </ul></td> </tr> <tr> <th valign="top"><p>Materials</p></th> <th valign="top"><p>Participants</p></th> </tr> <tr> <td valign="top"><ul> <li>Collaboration/brainstorming tool (whiteboard, flip chart, digital equivalent) </li> <li><em>AI Strategy and Discovery Presentation Template</em></li> </ul></td> <td valign="top"><ul> <li>AI initiative lead</li> <li>CIO</li> <li>Other IT leadership</li> <li>Senior business executives and managers accountable for AI initiatives</li> </ul></td> </tr> </tbody> </table> </section> <section> <h2>Sample ACME Corp Data<br> Example – Candidate AI use cases goal cascade</h2> <p>Customize this slide to reflect your business' goals, initiatives, and capabilities, and link them to your AI use cases.</p> <p><img src="https://cdn1-public.infotech.com/blueprints/Build-Your-AI-Strategy-for-Retail-Inventory-Management-Storyboard/example-candidate-ai-use-cases-goal-cascade.png" loading="lazy" width="1143" height="492" alt="an Example Candidate AI use cases goal cascade "> </p> </section> <section> <h2>Sample ACME Corp Data<br> Example – We identified common challenges & opportunities for candidate AI use cases in inventory management </h2> <p>Customize this slide to input possible challenges you may run into while implementing use case opportunities.</p> <table width="900" border="1"> <tbody> <tr> <td></td> <td><p><strong>Operational Efficiency</strong></p></td> <td><p><strong>Customer Experience</strong></p></td> <td><p><strong>Business Growth</strong></p></td> <td><p><strong>Employee Experience</strong></p></td> <td><p><strong>Risk & Resilience</strong></p></td> <td><p><strong>Environment, Social</strong><br> <strong>& Governance (ESG)</strong></p></td> </tr> <tr> <td><p><strong>Challenges</strong></p></td> <td valign="top"><ol> <li>Difficult to decide where to begin</li> <li>Data integrations complexity and model accuracy over time</li> <li>Employee resistance to new processes or automation</li> </ol> </td> <td valign="top"><ol> <li>Siloed systems that isolate data</li> <li>Real-time responsiveness to customer expectations</li> <li>High regulatory burden</li> <li>Need for data privacy/ security </li> </ol> </td> <td valign="top"><ol> <li>Large-scale transformation required to enable new AI powered tools/ capabilities</li> <li>Potential employee resistance</li> <li>Investment costs</li> </ol> </td> <td valign="top"><ol> <li>Transforming legacy process and tools to support the adoption of AI-based tools</li> <li>Siloed systems that don't work/work well together</li> <li>Siloed data</li> </ol> </td> <td valign="top"><ol> <li>Aggregating data required to capture and analyze risk data</li> <li>Developing comprehensive AI-based tools</li> <li>Potential regulatory complications</li> </ol> </td> <td valign="top"><ol> <li>Intensive process reengineering to implement AI tools</li> <li>Building of AI models/ tools to enable cost efficiencies</li> <li>Potential for employee dislocation </li> </ol> </td> </tr> <tr> <td><p><strong>Opportunities</strong></p></td> <td valign="top"><ol> <li>Significant infrastructure upgrades may be required to interconnect siloed system</li> <li>Data access/ aggregation will likely need to occur</li> <li>Data quality/data disparity between siloed systems will have to be addressed</li> <li>Reduction in manual time-consuming labor</li> </ol> </td> <td valign="top"><ol> <li>AI has the power to deliver personalized product and pricing recommendations</li> <li>Faster fulfilment through predictive analytics translates to reduced delivery times</li> <li>AI powered tools and processes can elevate customer experience by providing a consistent shopping experience</li> </ol> </td> <td valign="top"><ol> <li>As AI implementation grows, AI insights can help identify new and emerging product/ service opportunities</li> <li>Optimize the product portfolio by highlighting top-performing product and discontinuing underperforming product</li> <li>AI at scale supports competitive product, pricing, and promotion strategy</li> </ol> </td> <td valign="top"><ol> <li>AI tools can improve in-store shopping experiences</li> <li>Employees will be able to access more powerful/useful AI powered tools reducing the time to find and answer product questions</li> <li>AI can review/predict customer needs and generate customized outputs/materials with employee involvement</li> </ol> </td> <td valign="top"><ol> <li>Aggregation of operational performance data must occur to power AI tools</li> <li>New systems/vendors will likely have to be selected and implemented to power new operational data analysis to identify and quantify risk</li> <li>Potential for regulatory uncertainty and acceptance of AI based analysis/tools</li> </ol> </td> <td valign="top"><ol> <li>Potential to transform support functions within your retail organization to allow for customer/revenue scaling without linear cost growth</li> <li>Cost reductions leading to increased profitability</li> </ol> </td> </tr> </tbody> </table> </section> <section> <h2>3.1 Prioritize candidate AI use cases</h2> <h3>1-3 hours</h3> <ol start="1" type="1"> <li>Gather the AI strategy creation team and identify business opportunities that are high value to your business and its customers and have low implementation complexity/are highly feasible.</li> <li>Using the <em>AI Initiatives Prioritization and Roadmap Planning Tool</em>, leverage Tab 2, Initiative Planning, and transfer your candidate AI use cases list from Activity 2.1. </li> <li>Use the predetermined criteria or customize them for your own organization to assess candidate AI use cases by evaluating against the organization's mission and goals, the responsible AI guiding principles, and the feasibility of the project.</li> <li>As a group, score each candidate initiative based on its business value and feasibility.</li> <li>Ensure that candidate use cases that are to be automated align with the organization's business criteria and responsible AI guiding principles, and that you have the required resources to deliver the project.</li> <li>The tool will generate a prioritized list of initiatives and map them on the value/feasibility grid on Tab 4, Priority Grid. Once you've prioritized your candidate AI use cases, input this key list into your prioritized AI initiatives visual for your AI strategy on the <em>AI Strategy and Discovery Presentation Template</em>. This will help you to visualize the prioritized use cases as illustrated on the following page.</li> <li>Make sure you avoid sharing the organization's sensitive data if the application is deployed on the public cloud.</li> </ol> <table width="900" border="1"> <tbody> <tr> <th><p>Input</p></th> <th><p>Output</p></th> </tr> <tr> <td valign="top"><ul> <li>Candidate AI use cases list</li> <li>Organization mission, vision, and strategic goals</li> <li>AI vision statement</li> <li>Responsible AI guiding principles</li> </ul></td> <td valign="top"><ul> <li>Prioritized list of AI initiatives</li> <li>AI initiatives on value/ feasibility grid</li> </ul></td> </tr> <tr> <th valign="top"><p>Materials</p></th> <th valign="top"><p>Participants</p></th> </tr> <tr> <td valign="top"><ul> <li>Whiteboard/flip charts</li> <li><em>AI Initiatives Prioritization and Roadmap Planning Tool</em></li> <li><em>AI Initiatives Prioritization and Roadmap Planning Tool</em></li> </ul></td> <td valign="top"><ul> <li>AI initiative lead</li> <li>CIO</li> <li>Other IT leadership</li> <li>Senior business executives and managers accountable for AI initiatives</li> </ul></td> </tr> </tbody> </table> <p>Download the <a href="https://www.infotech.com/research/ai-initiatives-prioritization-and-roadmap-planning-tool"><em>AI Initiatives Prioritization and Roadmap Planning Tool</em></a></p> </section> <section> <h2>Leverage the Industry Reference Architectures</h2> <p>Use these templates to heatmap the maturity of capabilities relevant to your AI use case.</p> <p>The following templates are taken from the Industry Reference Architectures. </p> <p>Download a full copy for your industry for a more complete presentation.</p> <p>Download the <a href="https://www.infotech.com/research/ss/retail-industry-business-reference-architecture"><em>Retail Industry Business Reference Architecture Template</em></a><em>. </em></p> <p>Download the <a href="https://www.infotech.com/research/ss/wholesale-industry-business-reference-architecture"><em>Wholesale Industry Business Reference Architecture Template</em></a><em><a href="https://www.infotech.com/research/ss/wholesale-industry-business-reference-architecture">. </a></em></p> </section> </a.length;++i)if("function"==typeof(l=a[i])){l(e);break}}"function"==typeof>