4 Foundational Analytics to Become a Data-Driven Digital Distributor - Modern Distribution Management

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4 Foundational Analytics to Become a Data-Driven Digital Distributor

As distributors compete in an increasingly complex environment with non-traditional distributors amidst accelerating growth of digital channels and supply chain disruptions, using data (analytics and insights) to generate, manage and sustain profitable growth is becoming a key trait of resilient distributors.
Pricing, Sales, Profitability Top Priorities for Data Analytics

The distributor landscape has become far more complex with multiple go-to-market strategies, non-traditional competitors (such as online marketplaces), consolidation, supply chain disruption and demanding customer expectations. As the focus of distributor business models evolves from traditional brick-and-mortar to omnichannel presence, distributors must advance their decision-making process and the role of data in it.

In their pursuit of becoming digital distributors, many approach business analytics solely as a technology endeavor instead of seeing it as a catalyst to make better decisions. They miss the link between the business model and analytics. They choose advanced technology solutions without implementing foundational analytics or resort to inaction due to lack of clarity.

How can distributors leverage data – a strategic asset – to create analytics and insights, leading to profitable decisions? Which analytics are foundational and critical to the distributor business model? The options are plenty, but where should you start and how can you prioritize analytics efforts to become a data-driven organization?

Not all analytics are created equal. Here, we’ll discuss the core analytics you need to drive profitable growth and become a data-driven digital distributor within the context of our Growth Cube framework. This framework was the result of decades of comprehensive research on how distributors grow profitably and sustainably. Learn more about the Growth Cube framework in our article Checklists for Generating, Managing and Sustaining Growth.

Analytics for generating growth: customer analytics

According to our research and analysis, there are nine strategies distributors can use to generate growth successfully. These fall under the first dimension of the Growth Cube, Generating Growth. These nine strategies can be grouped into two buckets and are often used in combination with one another.

  1. Traditional growth strategies: Penetrate existing accounts, acquire new customers, introduce new products and services, open new branches and expand into adjacent market segments.
  2. Non-traditional growth strategies: Add a new go-to-market channel (such as ecommerce), create a new business unit by combining two or more traditional growth strategies, innovate your customer value proposition (such as multiple brands with different service levels), and diversify into adjacent verticals or value chain functions.

Though distributors may pursue a mix of the above strategies, the analytics that provide deeper insights to drive all growth strategies are customer analytics, powered or driven by customer stratification.

Customer stratification is the process of segmenting customers into micro clusters based on buying behavior. This is a quantitative exercise, leveraging omnichannel transaction data, not based on sales team perception or judgment. Customer analytics have become far more critical for sales teams, enabling them to implement these nine growth strategies amidst pandemic-induced constraints such as virtual selling.

Are you providing a sophisticated level of customer-specific information to your sales team to support their efforts to generate growth? Basic purchase history will not suffice, nor will an arbitrary sales goal-setting process that relies on last year’s performance. Give your sales force a higher granularity of customer data, the most useful of which will be past insights like product mix, margin trend and cost-to-serve, and future insights, like recommendations and opportunities.

Analytics for managing growth: inventory and pricing analytics

According to our research and analysis, two metrics emerged as pivotal for the Managing Growth phase, which involves achieving profitability while growing at above-average rates: gross margin and inventory turns.

We found a critical correlation between these two metrics across verticals. Let’s look at an example.

A large industrial distributor achieved 37% gross margin, while its direct competitor achieved 45%. The inventory turn is 4.5 for the former and two for the latter. The latter achieved the higher margin owing to its value proposition, which included providing far higher product availability of both core and non-core items. The former offered a higher fill rate for core items only. Both firms had different value propositions in terms of how they created value for their customers and captured customer value accordingly. The business models are different though they compete in the same vertical. We validated the correlation across other verticals and it holds true.

Two core analytics practices are critical to aligning how distributors create and capture value from customers: inventory stratification and pricing optimization.

Inventory stratification is the process of classifying items into micro clusters based on customers’ buying behavior such as velocity, volume and profitability. These core analytics provide the foundation for purchasing managers and buyers to make day-to-day decisions. Most distributors have access to inventory stratification analytics as part of their ERP system, but it’s often unidimensional and under-utilized.

The key in utilizing the core analytics discussed in this article is converting the analytics into playbooks aligned with the existing workflow of stakeholders (buyers, branch manager, category manager, supply chain planner and inventory coordinators). This results in better consumption of analytics to make day-to-day tactical decisions and avoid under- or over-investing in working capital.

Pricing optimization is the process of analyzing your transaction data across multiple factors (such as customer, item, visibility, supplier, volume, segment, etc.) to detect pricing opportunities at the customer-item-channel level. Pricing optimization is complex and granular, given item and customer proliferations as distributors grow both physical and digital footprints. The key is to integrate customer and inventory analytics with pricing rules and matrices.

Analytics for sustaining growth: customer and supplier analytics

You aren’t finished when you’ve planned for generating and managing growth, though many distributors don’t take this long view. We found the best way to determine how distributors can successfully sustain growth was to identify the reasons why growth stops or declines. The reasons generally came down to inaccurate assumptions made while generating and managing growth, and they fell into two buckets: opportunity assumptions and capability assumptions. If distributors miscalculate in these areas, or if they are negligent in making calculations in the first place, they quickly create blind spots that can derail growth.

Two critical blind spots fall in the “opportunity” bucket: customer retention assumptions and supplier alignment assumptions. To better calculate and understand these, you need two analytics: customer analytics (which we’ve already covered) and supplier analytics, using supplier stratification.

Supplier stratification is the process of using quantitative methods to segment suppliers based on spend, channel alignment, supply chain performance and profitability. The analytics shed light on the suppliers who are causing us to incur additional working capital due to delivery inefficiencies. It also helps distributors rationalize supplier and product portfolios by consolidating spend and aligning volume and profitability. As distributors grow, reliance on suppliers should be assessed (similar to customer churn and retention) to detect potential channel performance challenges and opportunities.

As distributors compete in an increasingly complex environment with non-traditional distributors amidst accelerating growth of digital channels and supply chain disruptions, using data (analytics and insights) to generate, manage and sustain profitable growth is becoming a key trait of resilient distributors. Keep your focus on creating and consuming these four core analytics as a starting point in your journey to becoming a data-driven digital distributor. When asked about the process of prioritizing between foundational and advanced analytics to build a data-driven organization, a distributor executive once said, “You need to clean the house before decorating.”

Senthil Gunasekaran is co-founder of ActVantage, which helps distributors drive profitable growth through analytics and talent development. He has more than 18 years of experience helping hundreds of distributors and manufacturers. He also delivers executive education and speaks at industry forums, and he recently compiled a guide to revenue recovery for distributors to use in navigating through the coronavirus pandemic. Prior to ActVantage, he led research and industry projects at Texas A&M’s ID program. Contact Senthil at senthil@actvantage.com or visit actvantage.com. 

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