Don’t Make This Critical Mistake when Addressing Tariffs

DC Velocity

Don't Make This Critical Mistake when Addressing Tariffs

Boston Tea Party

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.

Customer Segmentation based on Profit contribution

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 rsharpe@ci-advantage.com or visit our website at www.ci-advantage.com.

All the best,

Richard Sharpe
CEO – Competitive Insights

Build Profitable Tariff Strategies

DC Velocity

Build Profitable Tariff Strategies

Boston Tea Party

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.

The impact of global trade policies is a key element in establishing corporate strategies. It is critical 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 incoming 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: proactively work on multi-faceted tariff mitigation strategies such as Williams-Sonoma:

Short-Term Actions: react using a “one size fits all” strategy of price increases across their customer base. However, this type of action does not provide sustainable performance in maintaining or growing margin contributions. With the exact profitability of each customer and product, more targeted strategies can be implemented.

Formulate tariff strategies using the exact profit performance of every customer and every product. By tailoring your strategies to your best, marginal and unprofitable customers, you minimize the impact of tariffs.

Customer Segmentation based on Profit contribution

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:

  • 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. The incoming administration will waste no time in implementing the proposed new 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.

Competitive Insights has the ability, using Machine Learning and AI, to create accurate visibility to your current customer and product profitability. 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 rsharpe@ci-advantage.com or visit our website at www.ci-advantage.com.

All the best,

Richard Sharpe
CEO – Competitive Insights

Part 2: Create a Foundation of Repeatable Data Integrity to Fuel Your AI Solution

DC Velocity

Three Part Series on Smartly Avoiding the AI Hype Cycle

Part 2: Create a Foundation of Repeatable Data Integrity to Fuel Your AI Solution

Bad Data Leads to Bad Insights. Bad Insights lead to Bad Decisions.

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:

Diagrams on Data

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:

Brian Greene quote

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 rsharpe@ci-advantage.com or visit our website at www.ci-advantage.com.

All the best,

Richard Sharpe
CEO – Competitive Insights

Have a clear, intentional focus on the business problem you want to solve using AI

DC Velocity

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:

  1. Have a clear, intentional focus on the business problem you want to solve using AI (not a solution looking for a problem)
  2. Create a foundation of repeatable data integrity to fuel your AI solution (garbage in / garbage out)
  3. 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.”

-Soumen Ghosh, Mark Hersh, and Richard Sharpe - Supply Chain Xchange

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.

Product segmentation distribution chart

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.

Please comment on this posting or email me at rsharpe@ci-advantage.com

All the best,

Richard Sharpe
CEO – Competitive Insights

Case Study: HMTX





flooring manufacturer

a premier designer, manufacturer, distributor and marketer of resilient flooring

business challenge

to gain visibility into specific cost-to-serve and profit performance insights and opportunities across the product portfolio using Artificial Intelligence (AI) and Machine Learning (ML) technology



This project has been a perfect example of taking this new complex frontier of AI and boiling it down to a level of actionable results.
Brian Greene • Chief Supply Chain Officer • HMTX


solution

operational assessment & strategic capacity analysis

descriptive • diagnostic analytics
supply chain • finance

data assurance • cost to serve and profitability visibility • product segmentation • inventory




  • Data:
    provided the capability to have repeatable data integrity from siloed operating data for "One Version of the Truth"



  • Insight:
    highlighted differences between Standard/Gross Profit and Net Landed Profit Margin (9.64%)



  • Insight:
    demonstrated that over 1/3 of total SKUs were unprofitable



  • Insight:
    spotlighted the highest revenue performing SKU was unprofitable and the 5th worst SKU by Net Landed Profit



  • ROI:
    one pinpointed profit improvement area provided a 640% ROI for the entire project expenditure






The results illustrated in this case study are specific to the particular situations, business models, data input, and computing environments described herein. Each Competitive Insights (CI) customer’s experience is unique based on business and technical variables and all statements must be considered non-typical. Actual savings, results, and performance characteristics will vary depending on individual customer configurations and conditions. CI does not guarantee or represent that every customer will achieve similar results.

Putting AI/ML To Work – Smarter Cost & Profit Decisions

DC Velocity

Putting AI/ML To Work - Smarter Cost & Profit Decisions

Do you have trusted analytical insights?

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.

Please comment on this posting or email me at rsharpe@ci-advantage.com

All the best,

Richard Sharpe
CEO – Competitive Insights

Smartly Eliminate Roadblocks to Pinpoint Significant Cost Reduction Opportunities

S&OP with Profit
tackle supply chain stress

Smartly Eliminate Roadblocks to Pinpoint Significant Cost Reduction Opportunities

Roadblocks to Actionable Cost Reductions

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:

  1. 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.
  2. 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”.
  3. 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.
  4. 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.
  5. 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.
Top opportunities by product and customer

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.

Please comment on this posting or email me at rsharpe@ci-advantage.com

All the best,

Richard Sharpe
CEO – Competitive Insights

accurately understand SKU level cost and profit performance

Accurately Understand SKU Level Cost and Profit Performance

S&OP with Profit
tackle supply chain stress

Smartly Pinpoint Significant Cost Reduction Opportunities

Accurately Understand SKU Level Cost and Profit Performance

Smartly Pinpointing Significant Cost Reduction Opportunities

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.

In contrast, some progressive companies are taking a more proactive approach to reduce cost and operational complexity by doing a rigorous review of their product portfolio. (Osprey – Hydroflask: https://www.supplychaindive.com/news/osprey-hydroflask-helen-of-troy-supply-chain-overhaul/649176/ )

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:

Product Segmentation by Net Landed Profit Product Segmentation by Net Landed Profit

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.

Please comment on this posting or email me at rsharpe@ci-advantage.com

All the best,

Richard Sharpe
CEO – Competitive Insights

Smartly Pinpoint Significant Cost Reduction Opportunities

S&OP with Profit
tackle supply chain stress

Smartly Pinpoint Significant Cost Reduction Opportunities

Unwarranted Costs Associated with Unprofitable Customers

Reduce costs using Customer Profitability

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?

Customer Segmentation by Net Landed Profit

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.

Please comment on this posting or email me at rsharpe@ci-advantage.com

All the best,

Richard Sharpe
CEO – Competitive Insights

Smartly Tackle Data Barriers to Use Advanced Analytics

S&OP with Profit
tackle supply chain stress

Smartly Tackle Data Barriers to Use Advanced Analytics

Using AI/ML to Continually Reduce Operating Costs

Getthing through the Roadblock of Data

"less than half (44%) of data and analytics leaders reported that their team is effective in providing value to their organization"

“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.”

Lisa Harrington – President, lharringtongroup.com

Companies are struggling to use data and analytics to continually find ways to reduce operating costs and protect margins. 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”.

So why are so many companies still struggling with the adoption of Machine Learning / Artificial Intelligence (ML/AI) technologies to handle today’s inflationary pressures? The reasons can vary but some of the most common complaints are:

Our data still sits in silos and it is difficult to integrate.

We have pulled all our data together but people still don’t trust it.

As a large company, we have a long way to go to be able to support advanced analytics with the current state of our data.

Case In Point: A meeting was held with the CFO, COO and SVP of Supply Chain for a well-known apparel company. They knew that they needed to build analytical capabilities, but were skeptical because of their perception of the current state of their data. Fortunately, the SVP of Supply Chain had previous experience in working with a solutions provider in tackling this issue. He convinced the others to take a first step that would demonstrate that their data could be turned from a liability to an asset to produce meaningful insights on opportunities to reduce costs and increase profit margins.

Data Assurance

Action: A Project Team was assembled and all sources for their supply chain and sales transactional data were identified. Data Subject Matter Experts were involved to address any data issues. Consensus was reached by the Team on how the data should be intentionally transformed to build a foundation for SKU and Customer specific cost and profit performance information. ML/AI technology was then used to further validate data quality problems and to create specific and actionable financial performance insights that could be refreshed periodically. The Project team found a potential inventory working capital reduction in excess of $10 million dollars.

Data integrity issues can be proactively addressed to ensure that operating data becomes a valuable asset. An asset that allows for visibility into actionable insights that drive trusted, fact-based decisions. The companies that take this seriously will consistently move ahead of their competition and drive additional cost reductions and profitable performance.

Please comment on this posting or email me at rsharpe@ci-advantage.com

All the best,

Richard Sharpe
CEO – Competitive Insights