Mastering Metrics:

How to use traditional & AI-powered analytics to achieve objectives & maximize profit in the wholesale distribution business.

Harvard & Deloitte studies show that companies leveraging data analytics & AI see a 5-6% increase in profitability & greater market value.

The wholesale distribution of plumbing and HVAC products operates within a highly competitive marketplace. Distributors consistently battle against thin margins, evolving customer demands, and the ongoing complexities presented within the supply chain. Studies show that companies leveraging data analytics see a 5-6% increase in profitability, so let's dive into the power of metrics and reveal how they can drive your success.

It may seem that KPIs are something that you should just be able to pick up off the shelf and use, like a piece of software or a template. The truth is that KPIs are a detailed representation of your specific business and of your aspirations for your business.

Metrics empower decision-making. You can only manage what you can measure so well-crafted metrics that provide insights into the elements of your objectives and strategies are essential to accomplishing your goals. Actionable metrics provide focus and drive improved outcomes. This article lays the foundation for building a thriving data-centric wholesale business while introducing strategies for leveraging emerging AI tools that extract greater value from the abundance of data now available.

Building a Metrics-Driven Foundation?

The Why: Understanding the Power of Key Performance Indicators

An effective mix of KPIs should be both backward and forward-looking to provide meaningful guidance beyond simply measuring activities. Lagging KPIs yield critical insights from what occurred in the past while forward-looking objectives and result-oriented KPIs (sometimes referred to as OKRs) drive behaviour by measuring trends and progress. Both are needed to improve efficiency, increase profitability, boost customer satisfaction, and safeguard competitiveness. Wholesalers can quickly see areas where past processes or decisions succeeded so these successes can be repeated, or they can easily spot areas where a focus and change are needed. “A focus on measuring the right metrics & cascading them down to the entire team has allowed us to make improvements year-over-year due to the ability to see where gaps exist in productivity, customer loyalty, and bottom-line growth and take action to correct them,” says Mark Mininch, president of Marks Supply, A Marcone Company with over 60 years in plumbing and HVAC distribution in Toronto.?

In addition to key financial metrics, Mark breaks down his metrics in a way that follows the same path as the revenue in the company starting with quoting to win new projects, purchasing to maintain proper inventory levels based on demand, fulfillment to measure the efficiency of orders and customer service and logistics to ensure optimization of cost and service. For this article, I’ll reclassify these a little into similar but expanded categories of metrics: Senior Management Metrics, Sales & Customer Service Metrics, Quoter Metrics, and Warehouse Manager Metrics.?

Senior Management Metrics:

1. Inventory Accuracy and Turns:?Consistent control of inventory is key. This metric provides a vital snapshot of supply chain efficiency and working capital needs. Accurate inventory and timely turns prevent potential revenue loss caused by expired, slow-moving, or damaged products.
2. Fill Rate and On-time Delivery:?These metrics are essential for meeting customer needs. Distributors must understand fill rates and track how accurately and timely orders are delivered, as these are pivotal indicators of customer satisfaction and loyalty.
3. Customer Acquisition Cost (CAC) and Lifetime Value (LTV):?These metrics shed light on the overall return on investment of activities involved in attracting new customers. Wholesalers must consider if these acquisition costs make acquiring specific customer segments feasible and, ideally, identify the highest-value customers driving long-term profit.
4. Gross Margin and Profitability by Product Group:?A thorough analysis of the gross margin by product or product group offers a clear look at what product lines, suppliers, and even specific SKUs offer the greatest return. Knowing this data makes optimizing pricing or focusing sales and marketing decisions an informed process.
5. Operational Costs and Overhead:?These metrics measure overall business spending. An examination of overhead expenses and operating costs enables distributors to streamline their operations or pinpoint areas needing specific attention to maintain or enhance profitability.

Sales & Customer Service Metrics:

1. Sales Cycle Length and Win Rate:?These metrics track sales effectiveness. Monitoring the speed at which sales move through the funnel identifies issues in the process and offers insights for further optimizations. Win rate metrics are helpful when evaluating product pricing, the performance of specific sales channels, or when developing effective promotional or joint-rebate strategies. These measurements should be divided up by sales category (showroom, counter sales, commercial projects, etc…) and by region.?
2. Fill Rate and On-time Delivery:?Consistent fulfillment expectations influence customer satisfaction, and sales and customer service teams are at the front line of dealing with issues when expectations are unmet. Providing customer service teams with visibility into these metrics empowers them to take a proactive role in ensuring orders are filled and shipped on time.
3. Customer Satisfaction with Project Execution:?Projects may often be a one-time occurrence for the customer, so it's essential to focus on the experience for every job from start to finish. This customer satisfaction metric directly evaluates how successfully distributors manage project deliveries— ensuring future opportunities come back.

Quoter Metrics:

1. Quote Volume:?High quote volume indicates robust activity levels for the quotation team. Understanding quote volume is relevant because it shows if current staffing levels are adequately supporting sales goals. In contrast, tracking trends where quote volume decreases shows the need for possible pricing reviews or indicates there are gaps in relationship building efforts with contractors and engineers and designers.
2. Quote-to-Win Ratio:?A low quote-to-win ratio for commercial projects indicates issues with pricing, margin or profitability thresholds, or ineffective quote response times or follow-up. A strong quo-to-win ratio shows the mix or speed or response, product mix and availability is effective but don’t forget to look at win rate growth by contractor to determine if you are relying on too few customers for a large share of your work or if you can win and grow new contractors. Make sure you assess quote win rates by product category and brand as well to optimize relationships with your independent rep partners.
3. Quote Error Rate:?Minimizing errors in submitted quotes leads to better outcomes and avoids costly and time-consuming issues caused by rework. A high quote error rate could highlight quoter training is required or a review policy needs to be established. Imagine having a quote co-pilot that allows you to assess your finished quotes against company policy to ensure margin thresholds and profitability are maintined.
4. Average Time to Issue Quote:?Time to quote directly impacts the conversion rate, particularly in highly competitive sectors where customers may be comparing quotations from multiple suppliers. Ensuring speed and accuracy in pricing, proposal presentation, and delivery estimates directly improves the chances of winning a project.

Warehouse Manager Metrics:

1. Inventory Accuracy and Turns:?Inaccurate inventory numbers disrupt business operations. Warehouse managers, responsible for ensuring physical products accurately meet the numbers indicated within inventory management systems, can pinpoint process failures causing miscounts, misplaced items, or damage to prevent delays and lost revenue opportunities.
2. Fill Rate and On-time Delivery:?Fill rates are a clear indicator of a warehouse's effectiveness in having stocked items ready for timely customer delivery. Warehouse managers have notifications of demand for products right back to the quote stage to ensure fulfillment is ensured and out-of-stock situations are minimized or avoided. Inventory levels should also be visible at the time of quoting with clear alternative product suggestions as a backup option for low-stock items.
3. Change-order Frequency and Impact:?For jobs and large projects, last-minute changes by customers present complex planning disruptions. Understanding how often these happen and their subsequent impact offers critical data, indicating a need for improved communication between parties or the possible review of specific change order policies.

Converting Metrics into Scorecards for easier measurement of progress.?

The Power of Alignment

A metrics-focused framework reaches its full potential when KPIs are thoughtfully cascaded across all departments within the wholesale operation. Cascaded metrics support overall company goals by breaking down high-level objectives into smaller, actionable targets relevant to each team's work, but before we dive into how to create effective KPI it’s important to understand the difference between a dashboard with KPIs on it and a tactical scorecard where objectives are designed to be acted upon.?

Dashboards:

Dashboards are a collection of graphs, charts, gauges or other visual representations that are used to monitor the levels of the selected KPIs. The dashboard is used for monitoring operational activities and is not necessarily directly linked with the strategic directions of a company. Moreover, the dashboard usually provides an instant review of results and is constantly updated. Data available in dashboards is used to provide a foundation for better decision-making and more efficient day-to-day management of teams, resources, and expenses. For most organizations, dashboards present a high-level idea of an organization’s overall performance. Dashboards comprise multiple report types, allowing users to easily compare and contrast different reports or access diverse datasets within one business intelligence environment.

Tactical Scorecards:

Scorecards compare strategic goals with results. A tactical scorecard is used by employees to see where they are at in regards to their objectives on a daily, weekly or bi-weekly basis (whichever time frame makes the most sense for you). Tactical scorecards track KPI progress ie: comparing the current status of the metric being tracked and the target value and are perfect for ensuring people have actionable insight on whether they are on track to achieve their goals or even identifying problems and how they can be resolved.?

Difference Between Dashboard and Scorecards:

A dashboard is a performance monitoring system, whereas a scorecard is a performance management system. Using both will generate the best outcomes.

Scorecards are ideal when you’re looking for a concise view of a specific area. If you need to determine how well marketing KPIs are being met, or how a specific team handles their tasks, a scorecard can illuminate how close or far they are from their goals. This can be useful when you’re attempting to identify areas for improvement or ways to make specific tasks more efficient.

Dashboards are advantageous when you need a bird’s-eye view of your organization’s operations. Because they can hold multiple reports and data sets in a single hub, dashboards are highly useful when reviewing your success daily. Instead of specifically tracking progress toward goals, however, dashboards offer a more holistic view of data. That is, they present data without its target value, delivering a better historical view of progress which is ideal for making day-to-day operational decisions designed to improve your organizational processes.

Most importantly, your dashboards and scorecards don’t have to be separate entities. Many dashboards present scorecards as a periodic way to measure success, and they can also track KPIs. Scorecards can also be included in dashboards, offering an individual location to view multiple KPIs and their accompanying progress.

Crafting Role-Specific Scorecards

Translating broad KPIs into easily monitored scorecards customized for specific roles offers several key benefits:

• Clarity and Focus: Team members know precisely what areas impact success in their roles, prioritizing their efforts and decision-making on a real-time or at least a weekly basis.
• Accountability: Individuals understand and accept ownership of their specific performance targets.
• Empowerment: With transparent data at their fingertips, employees have increased opportunities to take corrective action or refine processes.

Let's examine practical scorecard examples across several typical wholesale distribution roles. These scorecards can be set up using a variety of software tools. See the sidebar for ideas and options on scorecard software options.

Scorecard Metrics for Sales:

1. Revenue growth: Measured against a specified timeframe (monthly, quarterly, annually).
2. New customer acquisition: Tracks the number of new accounts added vs. a goal.
3. Profitability per customer & profitability per product category: Focuses on high-value, long-term contractor clients and the products that drive the highest margin.
4. Project tracking and pipeline management: Emphasizes consistent movement of leads through the pipeline using clear conversion KPIs or milestones.

Scorecard Metrics for Customer Service:?

1. Order accuracy: Monitors misfilled orders, preventing rework and negative client experiences.
2. Customer issue resolution time: Emphasizes fast, effective responses to customer complaints.
3. Customer satisfaction surveys (CSAT) or Net Promoter Scores (NPS): Offer ongoing, direct customer feedback on the quality of service received.

Scorecard Metrics for Commercial Project Quotes:

1. Quote win rate: Directly affects profit and measures how competitive and profitable your bids are.
2. Quote margin: Set targets for the margin floor and assess won vrs lost against the target as well as margin by project category to help uncover trends in highly competitive project types.
3. Quote accuracy: Highlights the need for improved processes to provide clients with clear, realistic expectations.
4. Quote lead time: Focuses on getting competitive and accurate quotes into customer's hands as fast as possible.

Scorecard Metrics for Warehouse Managers:

1. Inventory turns: Reveals potential problem areas with slow-moving, obsolete, or near-expiration goods.
2. Picking efficiency: Impacts overall throughput and ability to meet promised shipping timelines.
3. Damage/loss prevention: Directly improves profitability by minimizing the need to write off stock due to damage.
4. On-time shipment ratio: Ensures goods leave the facility as specified to meet customers' expectations.

Important Note: These scorecard examples represent a starting point, offering guidance with ideas for tailored metrics that suit your wholesale distribution. It's essential to engage relevant stakeholders from each department when shaping their specific scorecards to enhance individual ownership and overall success.

Sidebar: KPI & scorecard tools

High-end capabilities but require IT and data analyst support to set up and manage:

1. Tableau
2. Power BI
3. Qlik
4. Omni.co
5. Databox.com

Mid-Range analytics tools. These are less technically complex and may not have all the cascading scorecard capabilities but they still provide excellent dashboards.

1. Domo.com
2. Retool.com
3. Grow.com

Simple starter platforms. These tools are flexible and do the trick for most small to mid-sized businesses. They are great options to get started in dashboard KPI and management.

1. Notion.so - Free version, with low-cost upgrades. Highly flexible.
2. Plusdocs - Collect snapshots of reports from various locations. Does not require data collection.

Methodology for building an easy-to-use Scorecard of the most valuable KPIs:?

To ensure everyone throughout the organization contributes to and reaps the benefits of a metrics-driven approach, I’m a fan of Bernie Smith from MadetoMeasureKPIs.com who recommends a value matrix exercise to help focus on the KPIs with the highest impact. Once you rank KPIs by Importance vs Availability, you should focus on the top right quadrant as this is where you will find a rapid return on your efforts:

Top right-hand box: The high-importance and easily available quadrant is the tranche of measures you put on your first dashboard/report. Easy to get and important, why wouldn’t you?

Top left-hand box: The high-importance and difficult-to-collect quadrant. The Aspire list becomes the ‘to-do’ list for your dashboard. This is where you focus your KPI development effort.

Bottom right-hand box: These are the trivial but easy to collect measures. It is worth double-checking any that border on important, but don’t get sucked into putting something on the dashboard or report simply because you can. A word of caution, the bottom right quadrant (Easy to get but trivial) can clog up reports and dashboards without helping.?

By the end of this exercise you should have divided your candidate measures into three:

• Do-it-straight-away list of measures - the Use list
• To-do list of measures to develop - the Aspire list
• Rejected measures (with reasons) - the Discard list

The Data Challenge: Metrics success depends on investing in data.

Running a modern plumbing distribution business generates a wide array of data across numerous functions. Data needed to create the KPI measurements lives across numerous platforms including the ERP system, the quote management tool, the warehouse management system, the CRM, and other systems such as project management software or showroom management. This fragmented storage often prevents a holistic view of all the variables needed to create and report on the metrics mentioned above, but don’t let this challenge stop you as the exercise of collecting, cleansing and aligning all the data will not only help you achieve the metrics objectives, but it will help uncover areas where efficiencies or enhancements in process and data collection are needed which will ultimately give you a better grasp on your company strengths and weaknesses.?

• Inefficient Decision-Making: Without connected data, it's challenging to gauge the bigger picture. For example, understanding the true stock levels of products used in quotations to realistically promise project delivery for customers requires integrated access across systems.
• Inconsistent and Redundant Data: The same customer information might exist in multiple silos, but without standardization, errors, mismatches, and duplicates hinder efficiency and may cause customer support issues.?
• Data Decay: Outdated, unused information residing within these silos leads to diminished returns as reliance on accurate and current data increases within every other process.

Strategies for Consolidating and Optimizing Data

Achieving a 'single source of truth' to fuel powerful insights takes focused strategies and requires a cross-functional team to ensure it is done properly. “The team at Marks Supply has a dedicated analytics leader that works closely with the IT group and the procurement group to ensure data from the ERP system, the quote system and the warehouse system are all accessible for reporting and scorecard purposes,” said Mark Mininch.?

?Several strategies to collect, clean and consolidate these disparate data points are available, ranging in complexity depending on individual distributor needs:

• Manual Data Integration usually involves exporting data from various systems, manipulating it in spreadsheets, and manually creating combined reports. This is labour-intensive but can provide some valuable insights into the nature of how your data is collected during the initial stages of creating KPIs as you may find some key points are missing that you hadn’t realized were unavailable for reporting purposes.?
• Data Integration Middleware: Specialized platforms offer connectivity between disparate systems. Middleware tools effectively pull data based on set schedules or specific triggered events and can then centralize the data.
• APIs (Application Programming Interfaces): With API availability, systems can "talk" to each other. Using specific queries that can pull predefined data fields across relevant systems opens up opportunities for more complex analytics while improving flexibility.
• Centralized Data Warehouse: A dedicated warehouse offers advantages for operations handling extensive data volumes. It allows for complex cleansing, organization, and data enrichment. Advanced analytical tools, including AI, can directly connect to these data warehouses.

Harnessing the Power of AI?

AI in Wholesale Distribution: Moving Beyond the AI Hype to Real Use Cases

Artificial Intelligence is a frequent headline for tech-savvy industries, yet its use cases still need pioneers who will test, iterate and refine the power that generative AI can bring. To get a real impact from AI, let's look at three main areas where AI could empower your distribution strategy:

• Demand Forecasting: AI excels at processing large volumes of historical sales data alongside external considerations like seasonality, and even emerging market trends. Uploading a historical transaction dataset to a Large Langue Model (LLM) AI platform like ChatGPT’s Advanced Data Analytics would allow you to “chat with your data” by asking the AI to review and recommend areas that it deems valuable so you can ask further questions about what the AI sees and get instantaneous answers and charts based on your questions.?
• Pricing Strategies: AI can analyze quote data to uncover win/loss rates and what the trends are regarding the price and margins for each project by region, by building type, by category and by customer. This will help you understand project price sensitivity and assuming you capture the names of the subcontractors, the general contractors, the architect and the design engineer, you can start to see patterns that you could influence to win more business through price adjustments, relationship building and product education.
• Anomaly Detection: AI is perfectly suited to help find anomalies in your financial transactions to ensure you’re protected from fraud of any kind whether internal, external, large or small.

Crafting AI Prompts: A practical approach to using LLM’s to gain insights into metrics and objectives

Harnessing large language model (LLM) AI tools such as ChatGPT or Google Gemini hinges on the quality of your prompts and guidance. I recommend OpenAI’s Enterprise ChatGPT subscription as it is the only version that does not use your data to train the language model. In other words, the data you upload there doesn’t leave your control. Let's use a few examples that relate to the discussion above:

Example 1: Identifying Correlations that lead to high margin business

• Problem: You want to review quotes, order entry and revenue data to find correlations that lead to higher profit margins. You want to do more business with customers that show high profit margins, but you need to understand if there are more correlations to the margins than just the volume of business.
• AI Prompt: "Act as a seasoned business analyst of a wholesale distribution company and analyze the attached project quotes, sales order and revenue data. Analyze profit margins by project to find correlations to things like the speed of project completion indicated by the time between the first and last order, or commonalities of who is involved in the project such as the engineer, general contractor and subcontractor. Look for other relationships that might seem to be influencing high-margin projects.”

Example 2: Identifying your most profitable segments

• Problem: You want to rank your most profitable areas by customer, product, brand, category, and region and get ideas on how to double down on what works.
• AI Prompt: "Act as a financial analyst with experience in wholesale distribution of plumbing products. Please analyze the attached sales and cost data to identify key areas of profitability. Provide a prioritized list of the top three areas where I should double down my efforts to sell more and the bottom three areas where I should consider improving or eliminating my sales efforts. Ask me clarifying questions if you are not clear on any of the data points."

Example 3: Inventory optimization and brand alignment percentage.

• Problem: I need to assess my inventory against market demand trends to look for things like overstocked items, high turnover vs. low turnover products and trends in dominant brands that are being specified as the basis of design compared to what brands I have in inventory.
• AI Prompt: "Analyze the attached quote, order and warehouse shipping data to identify and mitigate risks related to inventory management, focusing on the following key areas: Segment A: Overstock Analysis: Identify items that are overstocked by comparing current inventory levels to historical sales data. Highlight products with the lowest turnover rates as potential overstock risks. Segment B: Calculate and rank items by their turnover rate to identify high-performing products. Use the formula Turnover Rate = Sales Volume / Average Inventory for a specified period to assess efficiency in inventory management. Segment C: Brand Specification Trends: Analyze the trends in brands that architects or engineers are specifying as the basis of design in projects compared to the brands currently held in inventory. Identify mismatches where specified brands are underrepresented in the inventory, indicating potential missed sales opportunities." Let me know if I am missing data points required to perform these calculations and if there are other inventory optimization calculations that I may be missing.”?

Important Note: AI responses shouldn't be followed blindly. It is essential to have subject matter experts evaluate the outputs to ensure validity and refine further analyses based on findings. AI serves as a tool to generate new perspectives and identify patterns humans might miss due to sheer data volume.

Side bar: How to start using ChatGPT’s Advanced Data Analytics:

1. Get a Team or Enterprise subscription to ChatGPT
2. Prepare and Organize Data: Clean the data by removing inaccuracies and organizing it in a structured format in a spreadsheet or a database to allow for analysis. Finding a point of connection such as transaction number or UPC code is essential when you combine data from different sources, otherwise, you will need to create a unique identifier to complete the required data point connections and correlations.
3. Develop Custom Prompts: Create specific prompts for ChatGPT that align with your business goals. You can ask ChatGPT to help you write prompts to get you started.
4. Integrate ChatGPT with Business Systems: Find analysis tools that have ChatGPT built-in or find a no-code developer to help you write an automated workflow for AI analysis.
5. Test & iterate until you get the outputs you want: the most challenging part of deploying AI for data analytics is getting the data cleansed and formatted in a way that AI can read and understand it. Test and make changes to the data output and format to allow the AI to read and understand the data because once you have it formatted correctly, the insights AI can provide will be well worth the effort to clean the data in the first place.

Conclusion?

Embracing a metrics-oriented approach in wholesale plumbing and HVAC distribution paves the way to heightened adaptability, efficiency, and long-term growth. This article outlined the importance of aligning KPIs with strategic goals, provided tools to measure performance across crucial functions within a wholesale operation, and gave guidance for breaking down data silos to increase insights and support AI exploration.

With a commitment to data-driven decision-making, enhanced by the emerging power of AI, successful wholesale distributors will remain on the cutting edge of a highly competitive industry. As data-gathering processes refine, new business challenges are tackled, metrics shift and technology innovations arise, this iterative data-driven approach remains core to continued success.