3 ways to manage cash flow through data analytics

Every distributor should regularly review cash flow to help ensure the highest level of financial vitality. Maintaining a clear picture of this important metric not only helps ensure operational continuity but also allows distributors to capitalize on growth opportunities.

For those who may not have a robust management process in place, the good news is that data analytics offers the opportunity to analyze existing data to uncover important insights. Data analytics can help businesses understand and manage sales, inventory, accounts receivable and customer segmentation.

There are several key considerations to take into account when managing your cash flow. These variables can impact your inventory decisions, supply chain strategies and ultimately your sales figures and customer satisfaction.

What should your business consider when making strategic decisions about your cash flow?

Key cash flow variables

1. Inventory

Maintaining optimal inventory levels is key to cash flow management. To optimize inventory, it is important that distributors can effectively anticipate inventory issues such as deadstock, supply mismanagement or wasted inventory. The analytics begin with some tough questions:

How well does the business understand the supply chain? Distributors who clearly understand their supply chain can streamline processes, reduce bottlenecks and optimize their inventory. This efficiency translates to cost savings and better customer service.

What if one of those in the chain falters? Awareness of supply chain components, from suppliers to end customers, helps distributors identify vulnerabilities. Continuity can be maintained by proactively addressing risks, such as disruptions or quality issues.

For the purposes of cash management, and also to deliver on commitments to loyal customers, good data analytics practices can help distributors understand:

• What is needed?
• When will it be needed?
• When will it be delivered?

With good quality data, analytics can also predict when inventory is approaching depletion so distributors can work with customers to offer substitutes or delay orders. Data analytics enables insightful decision-making about:

• Ordering appropriate quantities.
• Reserving stock for particular customers.
• When it makes sense to acquire a new business.
• Most-effective communication strategies.
  
  

2. Customer and product segmentation

Successful cash flow is also determined by how well businesses know existing customers and product profitability. A data-driven analysis allows for line of sight to the big picture as well as transactional details.

A traditional customer profitability analysis distorts reality by applying an average cost allocation to all products and customers when, in reality, different products drive different holding costs and different customers drive variable levels of servicing costs. Often these differences are significant.

• Analytics make it easy to drill down to transactional details and trace costs to specific products and customers.
• It then becomes easy to determine which products and customers are driving profitability and those that are hindering it.

Traditional customer profitability analyses often lead businesses to discontinue entire product lines or sever ties with customers who appear unprofitable. Analytics provide the opportunity to make better cash flow decisions by:

• Performing what-if analyses on key variables.
• Understanding the exact combinations of purchasing scenarios and sales circumstances that consistently produce the best outcomes for the business.

Better-informed decisions to discontinue products or sever ties with customers can now be made with much more useful information. Conversely, insights about the most profitable products and customers can also materialize.

3. Receivables

Data analytics can help management understand how internal policies and processes are impacting the collection of outstanding invoices. Even in situations without economic uncertainty, businesses can become complacent when it comes to receivable management. Data analytics can help in this area by:

• Pairing receivables with invoicing programs to help ensure prompt delivery.
• Predicting payment dates for those with a history of delinquency, thereby improving the accuracy of cash flow statements.
• Identifying situations where it makes sense to offer discounts to incentivize timely payment.

How Wipfli can help

Data analytics offer the opportunity to not only identify trends and opportunities with existing policies and practices but also open the door to a deeper understanding of important trends with customers, suppliers and more.

If you’re ready to optimize your analytics practices, contact us today. Our dedicated professionals can help you leverage the latest business intelligence tools to improve your operations, get a handle on your data and manage your cash flow better.