How Data Helps Distributors Overcome Profit-Squeezing Obstacles - Modern Distribution Management

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How Data Helps Distributors Overcome Profit-Squeezing Obstacles

The right data analytics can help distributors avoid falling behind the competition.
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Distributors face profit-squeezing challenges everyday:

  • Salespeople who act more like lone wolves, with too much leeway on pricing and customer focus;
  • The tendency to treat all sales the same, with a cost-plus philosophy regardless of customer size or type;
  • A resistance to technology, waiting until they have no choice but to upgrade.

Independent distributors will always be up against larger national distributors with greater scale, fending off an increasingly rapid race to the bottom on price. But how can distributors overcome these obstacles to protect and grow margin in the market, while expanding market and wallet share?

They need data. The right analytics can help distributors avoid missing opportunities and falling behind the competition.

Take, for example, technology that allows sales teams to be more productive, helping salespeople spend more time engaged in activities that could lead directly to increased sales and margins rather than tracking down the best contacts and qualifying leads. In fact, sales and marketing research firm TOPO studied companies with high sales growth, and found that sales reps at those companies received 60% more support, including lead qualification, operations and sales enablement, than those at low-growth companies. So, when it comes to sales effectiveness — or getting the most out of one of your more expensive resources — data matters. And solutions have emerged that allow distributors to get these benefits without spending hours pulling data and crunching numbers.

Another area where data can help distributors compete profitably is in operational efficiencies. By analyzing historical buying patterns, it’s easier to forecast future needs, allowing distributors to operate proactively rather than react to orders and purchasing patterns. Machine learning takes the insight one step further, providing data on not just what customers buy, but also who they are and when and how often and even why they buy your products. It can also tell you when customers might need to restock or even be ready for additional or upgraded product.

There are four types of analytics that can help distributors overcome common challenges to growth and profitability:

1. Descriptive: Descriptive analytics involves reporting, or summarizing existing data on what’s already happened for insight. New visualization tools make data more accessible and interesting, and even actionable, showing data on a map or providing drill-down capabilities that might be hard to get from a big report. This represents the vast majority of analytics.

2. Diagnostic: Diagnostic analytics answer why, by identifying patterns and relationships between data. For example, there may be a correlation between weather and sales.

3. Predictive: Data in the past is known and can be measured, but data in the future can only be estimated. Predictive analytics use algorithms to estimate unknown data. This includes things such as weather forecasting and demand forecasting. This helps distributors make educated decisions about how to respond, perhaps by increasing inventory to meet expected demand.

4. Prescriptive: This is the most exciting of the four categories of analytics. Prescriptive analytics recommends an action based on the prediction to optimize a business outcome. For example (from our everyday life), GPS will use descriptive analytics (roads and speed limits), diagnostic analytics (what’s causing backups), and predictive analytics (what traffic flow will be like by the time you get there), to recommend the most efficient route. An example of prescriptive analytics for distributors would be data that might tell them which delinquent accounts collection agents should be calling based on the likelihood they would pay.

Together, these analytics models can guide distributors to the best decisions for how they go to market, which customers they target, how they price their products and services, and other long-term strategies. The goal is to leverage this data to reduce the cost of going to market through improved efficiencies, while increasing the effectiveness of your effort.

This is No. 10 of MDM’s 10 Most-Read Blogs of 2019. Each week as the year winds down, we will share these most popular posts until we reach No. 1.

Sean Kracklauer is chief revenue officer for ENAVATE, a Microsoft Dynamics 365 partner focused on the wholesale distribution industry. For more than 25 years, he has been assisting Global 1000 businesses on strategy, revenue acceleration, organizational structure, technology implementation and process redesign. Kracklauer has worked extensively in corporate strategy, sales management, global business services, ERP implementation management, and business process outsourcing. Reach him at

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