At a recent Executive Finance roundtable in Atlanta, a clear theme emerged: AI works when it solves real, costly problems—not when it’s applied for novelty.
This discussion was not merely another debate on AI; it was a collaborative exploration of how Finance leaders can leverage technology to enhance execution while preserving trust, discipline, and human judgment.
Three key takeaways:
Data accuracy is paramount. Attendees expressed concerns about the risks associated with unreliable and fragmented data.
The Finance role is evolving. Finance leaders are expected to go beyond reporting outcomes but influence decisions with actionable cost and profit insights that help guide the enterprise with clarity especially in volatile times.
Automation and AI serve different purposes. Process automation can eliminate repetitive tasks. AI can enrich analytical insights to provide greater financial visibility that supports clear business needs.
The conversation reinforced an important reality: analytics alone do not drive outcomes. Cross-functional collaboration depends on trust, credibility, and the ability to translate insights into action.
If you work in finance, FP&A or corporate strategy, check out our latest 2-minute YouTube discussion on “Cost & Profit Insights Driving Cross-Functional Collaboration”
Also, join us on June 2 for our upcoming webinar: “From Fragmented Data to AI-Driven Decisions: How Supply Chain Finance Leaders Are Fostering Cross-Functional Discussions to Reduce Costs and Safeguard Profits.”
The interactive session will explore how supply chain finance leaders are fostering cross-functional discussions to reduce costs and safeguard profits, securing their place at the decision-making table.
Thought the speakers did a great job looking past the hype from two really popular topics – #Tariffs and #AI , and instead focusing on practical applications. Richard Sharpe reminded us that tariffs are just one cost variable that go into your Net Landed Cost equation. -LinkedIn post from Matt Labagh
At the first Annual Conference for the San Diego Association for Supply Chain Management (ASCM) Conference, Richard Sharpe delivered the Keynote presentation to a standing room only event. The highly interactive discussion offered recommendations for developing informed tariff mitigation strategies. Strategies empowered by accurate, specific and actionable product, customer and supplier Cost to Serve and Profit performance insights. Strategies that out perform general price increases.
Examples were offered for the following short term, intermediate and long-term strategies:
Short Term (6 weeks) – because tariffs are only one line item of cost, pinpointing specific revenue and cost improvement opportunities for unprofitable Products can more than offset any increase in tariffs while improving the performance of unprofitable Products.
Net Landed Cost to Serve line items highlighting tariffs
Intermediate (6 months) – benchmarking cost and profit performance for Customer and Product categories can identify substitutable Products that have a better profit profile even with increased tariffs.
Forecast of one Unprofitable SKU historically, forecast doing nothing with increased tariffs and forecast after changing supplier
Long Term (2 years) – understanding the profit contributions for specific Products sourced from each Supplier can help prioritize Procurement resources on the Suppliers and Products that matter the most when developing tariff mitigating strategies.
Competitive Insights is an industry recognized leader in providing trusted AI solutions. Solutions that offer visibility on cost and profit performance specific to Products, Customers, Channels, Inventory, Pricing and the impact of tariff strategies.
This visibility provides fact-based insights on how you can mitigate costs and identify the best options to protect margins and profitable performance including tariff mitigation strategies.
We would love to hear your thoughts and comments. Please feel free to reach me directly at [email protected] or visit our website at www.ci-advantage.com.
Three Part Series on Smartly Avoiding the AI Hype Cycle
Part 3: Successful Adoption of AI Solutions
“I’ve experienced many technology implementation projects. Successful AI solutions recognize the need to quickly deliver significant value while minimizing resource requirements.”
Scott DeGroot • former VP, Global Planning and Logistics • Kimberly-Clark Corporation / Lecturer at the GSCI at the University of Tennessee
This is Part 3 of a series offering the following three tenants to avoid experiencing the Artificial Intelligence (AI) Hype Cycle:
Manage the adoption of AI/ML solutions to provide rapid, repeatable and actionable results (not boiling the ocean)
Capital and human resources investments in pursuit of AI solution can be significant. Selecting the right AI approach can be a daunting task. It is essential that guidelines are set for AI adoption journeys. The following three basic considerations can help guide companies manage the adoption of AI/ML solutions to provide rapid, repeatable and actionable results:
Rapid Results – rapidly solving a critical business problem builds confidence and momentum in adopting AI solutions. Organizational disillusionment and reduced future investments arise when measurable results require extended deadlines.
Repeatable Results – One time “project” approaches are difficult to justify. Starting with a well defined Pilot for a repeatable solution can significantly increase internal buy-in by demonstrating significant measurable value.
Actionable Results – results have to be accurate, trusted and specific in order for the organization to take action based on the results. Otherwise, adoption of the solution will meet resistance and likely fail.
The following table is an example of actionable results from a rapid and repeatable solution. The table pinpoints the top 5 profit enhancement opportunities by specific SKU and channel.
The significant promise of the potential value of AI solutions is clear. The path for adoption that avoids the typical “Hype Cycle” should start with:
A clear focus on the problem to be solved
Investment in data integrity to drive the solution and
Requiring strong, repeatable financial returns
Competitive Insights is an industry recognized leader in providing trusted AI solutions. Solutions that offer visibility on cost and profit performance specific to products, customers, channels, inventory, pricing and the impact of tariff strategies.
This visibility provides fact-based insights on how you can mitigate costs and identify the best options to protect margins and profitable performance.
We would love to hear your thoughts and comments. Please feel free to reach me directly at [email protected] or visit our website at www.ci-advantage.com.
Don't Make This Critical Mistake when Addressing Tariffs
Companies must act now to gain an accurate, specific and actionable understanding of each customer’s and product's performance to successfully protect and grow profits.
Historically, companies have made the critical mistake of using customer price increases to offset the costs of tariffs. With the tariff increases being designed by the new Administration, it is important to diversify tariff actions based on accurate, specific and actionable insights on each customer’s and product’s profit contribution. Those insights can be gained quickly to successfully continue to protect and grow profits.
The impact of global trade policies is a key element in establishing corporate strategies. It is important to recognize there are both short-term (weeks) and long-term (years) considerations in protecting profitability from tariff increases.
Protectionism versus free-trade policies have long been a part of political landscapes. I am not advocating the pros or cons of the utilization of tariffs. However, the new administration’s position on levying new tariffs will significantly impact revenue growth and potential earnings for many companies. In response to tariff increases, companies typically perform the following:
Long-Term Actions: determining the end-to-end implications of tariff increases on suppliers, manufacturers and distributors. Then, this information is used to develop multi-faceted tariff mitigation strategies such as the following example by Williams-Sonoma.
Short-Term Actions: making the critical mistake of reacting using a “one size fits all” strategy of price increases across their customer base. This type of action does not provide sustainable performance in maintaining or growing margin contributions.
Short and long-term tariff strategies can be far more effective knowing the specific profit contributions of every customer and product. This knowledge provides for diversified strategies based on high, marginal and unprofitable performance. In addition, these actionable insights can be applied in a matter of weeks as the political landscape shifts and turns.
Based on years of Competitive Insights client findings, customers can be grouped into the following three performance segments:
The very small number of customers that provide 95% of the profit (Critical)
The majority of customers that provide only 5% of the profit (Marginal)
The customers that are totally unprofitable (Unprofitable)
Tariff strategies can then be based on informed actions for each performance segment:
For Critical customers, some price increases may be needed, depending on the product mix purchased. The key is to ensure tariff related strategies prioritize keeping a strong and robust business relationship.
For Marginal customers, it is imperative to understand what is driving their performance (sales volume, pricing, discounts, etc.). This root cause analysis can then be factored into tariff mitigation strategies for each customer.
Unprofitable customers are only going to be more unprofitable if nothing is done. They should be carefully examined to understand why they are not generating net profitable performance. Corrective actions need to also include the additional negative impact of new tariffs.
Formulating profitable tariff strategies must be based on a specific understanding of profit contributions by customer and product.
Companies must act now to gain an accurate, specific and actionable understanding of each customer’s performance to successfully protect profits.
Competitive Insight’s AI solutions can create accurate visibility to your current customers and portfolio profitability in weeks. This visibility provides fact-based insights on how to best mitigate tariff increases to protect margins and profitable performance.
We would love to hear your thoughts and comments. Please feel free to reach me directly at [email protected] or visit our website at www.ci-advantage.com.
Three Part Series on Smartly Avoiding the AI Hype Cycle
Part 2: Create a Foundation of Repeatable Data Integrity to Fuel Your AI Solution
This posting is part of a three part series on smartly avoiding the AI Hype Cycle. Part 1 of this series “Have a Clear, Intentional Focus on the Business Problem You Want to Solve” can be accessed here.
Creating a foundation of repeatable data integrity is absolutely essential to have a sustainable AI solution that provides ongoing value. However, companies continue to struggle with data issues. According to Gartner:
“Less than half of data and analytics (D&A) leaders (44%) reported that their team is effective in providing value to their organization.”
Companies have made investments to improve their data environment but still have not realized the attributes that they need. For data to be actionable it must be Accurate, Specific, Trusted and Repeatable. Instead, companies discover that their data remains Siloed, Fragmented, Missing or the right data is Difficult to Obtain. The required transformation is depicted in the following diagram:
Lisa Harrington, President of the Harrington Group, summarizes the issue with the following:
“Harnessing the true power of data driven insights is the holy grail of future business. A wealth of this data comes from the supply chain. But, while the information is there, companies are not yet capitalizing on its real value as a source of insight capable of shaping the future of the enterprise.”
Let’s further define the characteristics in the diagram above that are required to create a foundation of repeatable data integrity. The data must be:
Accurate – use a 3-step process incorporating Machine Learning to ensure the accuracy of supply chain data;
Data Recognition – repeatable data sources have been agreed upon
Validation – detailed data values and data patterns have been analyzed
Verification – functional transactional data has been approved by SME’s
Specific - minimize data approximations or allocations whenever possible
Trusted - take the time to verify the organization trusts the information that you are using for your AI solution
Repeatable - require your data solution to provide for frequent refreshes that meet the other three requirements
One aspect of AI, Machine Learning (ML), positions companies to harness the full potential of their supply chain related data. In the attached video from a recent Georgia Tech conference, Brian Greene offered the following:
The frustration associated with data issues can be solved. Ask any Executive if they would like to have better, more insightful, cost and profit performance visibility based on trusted and repeatable data. I guarantee the answer will be YES!
The power of AI can deliver cost and profit performance visibility that continually adds “disruptive” competitive advantage.
The third part of this series will address Manage the Adoption of AI/ML Solutions to Provide Rapid, Repeatable and Actionable Results.
We would love to hear your thoughts and comments. Please feel free to reach me directly at [email protected] or visit our website at www.ci-advantage.com.
Three Part Series on Smartly Avoiding the AI Hype Cycle
Part 1: Have a Clear, Intentional Focus on the Business Problem You Want to Solve
“I continue to be impressed by the system.”
John Elliot • Former SVP of Operations • Hospira
Many companies are struggling to find the value (the “beef”) in Artificial Intelligence (AI) / Machine Learning (ML).
Companies are forecasted to spend $407 Billion on AI/ML technology in 2027 up front $86.9 billion in 2022 according to Forbes. As companies invest in the latest technology, they find that their expenditures have been influenced by typical hype cycle expectations.
This frustration can be avoided by following these three adoption cornerstones:
Have a clear, intentional focus on the business problem you want to solve using AI(not a solution looking for a problem)
Create a foundation of repeatable data integrity to fuel your AI solution (garbage in / garbage out)
Manage the adoption of AI/ML solutions to provide rapid, repeatable and actionable results (not boiling the ocean)
The focus of this three-part series is to help companies avoid the hype cycle in AI investments. Investments that empower an organization to have game changing cost and profit performance insights for every product sold to every customer through every channel.
Part 1: Have a clear, intentional focus on the business problem you want to solve using AI
Companies have long recognized that having high-level cost and profit details, based on allocation methods, do not support making the critical types of decisions that are required in today’s competitive marketplace. The following highlights come from an article published by Clorox, Georgia Tech and Competitive Insights:
“Grouping customers by their revenue contributions or products based on their market category is commonplace. But zeroing in on discrete segments based on their exact contribution to bottom-line profits is another matter.”
“To be actionable, the profit contributions must be based on the actual realized net revenue for each product sold to each customer as well as all costs required to service that order from the sourcing of the product to the order-fulfillment activities.”
This was certainly the case for Hospira, a pharmaceutical company. The Executives realized that they needed to have complete end-to-end visibility of the costs associated with their complex product portfolio. The following provides a summary of the segmentation of their products based on accurate and specific profit performance for every product being sold.
The company gained such incredible value from these insights that they directed the data to be refreshed regularly.
“I continue to be impressed by the system.” – John Elliot, former SVP of Operations, Hospira
Ask any Executive if they would like to have better, more insightful, cost and profit performance visibility and I can guarantee the answer will be YES!
Following these cornerstones, the power of AI can deliver cost and profit performance visibility that continually adds “disruptive” competitive advantage.
Putting AI/ML To Work - Smarter Cost & Profit Decisions
One of the world’s most iconic brands announced they would reduce the number of brands in their portfolio by 50%. James Quincey, CEO of The Coca-Cola Company, stated in The Wall Street Journal: "Now is the time for Coca-Cola to cull the portfolio of the many small, less profitable, resource-depleting brands"
“All told, the 200 brands slated to be discontinued account for only about 1% of the company’s profits. They consume too much attention and resources.” Atlanta Journal Constitution October 22, 2020
With growing inflationary pressures, companies are pursuing aggressive strategies to reduce costs and operating complexity while still delivering expected profit contributions and shareholder value.
One prime area of focus is Portfolio Management.
Progressive companies are taking a proactive approach to reducing cost and operational complexity by performing a rigorous review of their product portfolio:
The Executive Vice President for a U.S. based company was dealing with significant cost and complexity pressures. His solution was to focus on the impact of SKU proliferation; "can we measure the specific cost and profit performance at the SKU, Customer, Channel and Region levels to reprioritize resources?”
Working with Competitive Insights, his organization discovered:
Only 3% of their entire Customer base was contributing 80% of their profit
45% of their operating costs were being spent on servicing unprofitable customers and products
Their 11th largest Customer, measured by Revenue contributions, was totally unprofitable
Having accurate, specific and trusted Cost and Profit performance insights produces actionable strategies that have extremely positive results.
Smartly Eliminate Roadblocks to Pinpoint Significant Cost Reduction Opportunities
Many innovative companies are supporting their supply chain leaders in spearheading approaches to capitalize on Artificial Intelligence (AI) and Machine Learning (ML) to reduce costs and protect operating margins.
However, laggard companies are experiencing internal resistance to adopting solutions that deliver accurate and specific SKU, Customer and Channel cost and profit performance insights.
The following statements come from hundreds of frustrated Supply Chain Executives:
Our data is bad, missing, fragmented, siloed and managed in different systems.
The power of AI and ML can be harnessed to eliminate the burden of connecting, validating and transforming data from multiple operating systems. In addition, significant data validation can be done efficiently by pinpointing possible data issues to Subject Matter Experts within a company.
We have a hold on outside expenditures.
Cost containment is a primary mandate for companies during inflationary business cycles. This unfortunately means that companies try to maintain their current operation by reducing any possible discretionary expense. This position indirectly discourages the use of innovation to reduce costs. Having the knowledge of where to focus on the most effective cost reductions will provide far more opportunities than just “tightening the belt”.
We are just too busy and have very limited resources.
AI / ML advancements can greatly simplify the ability to have unified and trusted information that can be used cross-functionally to make better enterprise-based decisions instead of departmental, siloed decisions.
We can do this ourselves.
Companies that undertake this type of development effort often experience unanticipated, longer development timeframes and higher personnel costs. Business Intelligence (BI) tools are very useful but are not designed to handle the required volume of transactional data (typically 4 billion+ transactions). The result is often organizational frustration and extended timeframes to achieve significant ROIs.
We tried doing this before and it didn’t work.
Only one or two companies have the supply chain, data analytics and data governance knowledge and experience. Add the need for AI/ML knowledge and it clear why internal efforts fail.
The companies that are successful at creating specific, accurate and actionable cost and profit performance insights will be the winners in the next decade. Companies must overcome organizational roadblocks to taking advantage of ongoing AI/ML advancements like generating specific, accurate and actionable cost and profit performance insights.
The reality is that having this type of information on a continuous basis has become table stakes to accelerating a company’s growth and gaining market share. Allowing excuses to prohibit the adoption of these strategic advancements is a dangerous competitive disadvantage.
Accurately Understand SKU Level Cost and Profit Performance
37,825 unprofitable products adding $608 million in operating costs and draining $146 million from the profitable performance of the company
Companies are pursuing aggressive strategies to reduce costs and operating complexity while still delivering expected profit contributions and shareholder value. Using price increases, package down-sizing and re-negotiating supplier agreements can have damaging, long-term impact on customer and supplier relations.
Another case in point is for a well-known global company that continued to increase the size of its Product Portfolio sold through three different Channels. The global Head of the Supply Chain knew that this was adding operational complexity and costs. He also knew that the answer to solving this problem was to gain accurate, specific and repeatable cost and profit performance for every SKU in their portfolio.
As with most companies, this company had a host of data sources that were siloed and difficult to use. Having previous experience with these issues, he charged his organization to find a solution that was scalable and that would provide a significant ROI every month. A solution was selected and found the following results:
As you can see, there were 37,825 unprofitable products adding $608 million in operating costs and draining $146 million from the profitable performance of the company.
Inflationary pressures are a significant concern for all companies. Understanding the ROI on where a company’s resources are being applied is critical as it relates to the actual costs being applied to servicing Customers, Channels and Regions and their Product orders. Having accurate, specific and repeatable insights to Cost and Profit performance produces actionable strategies that have extremely positive results.
Unwarranted Costs Associated with Unprofitable Customers
This change dropped $3 million dollars off of their Outbound delivery costs.
Everyone of your customers provides a specific profit contribution to your Quarterly Earnings. It may be very positive, marginal or negative. Clearly knowing and trusting profit performance information at the Customer / SKU level goes beyond what is typically available in a P&L Statement. Having this information on a repeatable basis can lead to actionable strategies on sourcing, pricing and customer related operating costs. For most companies, not having this information leads to a “one size fits all” approach.
A previous client had a typical complex supply chain network of manufacturing locations, D.C.s, local service centers, their own private fleet and third-party service providers. Their network serves 110,000 customers across the United States. Want to guess how many customer locations provided 80% of their operating margin on a repeatable basis?
As shown in the chart, 2,843 customers provided 80% of their recurring profits. 106,362 were very marginal contributing 20% and the remaining 40,517 were unprofitable draining ($5 million) off their yearly earnings.
The Executive Team immediately identified 24 new operating strategies based on the financial performance insights that were provided. One of them was to no longer offer next day service to unprofitable customers.
This change dropped $3 million dollars off of their Outbound delivery costs.
