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Analytics Articles for Business, Supply Chain and HR

Analytics Articles: Human Resources, Supply Chain, Diversity and Business Analysis

Numerical Insights publishes articles on a variety of topics including business analytics, data analysis, data visualizations tools, improving business results, supply chain analytics, HR Analytics, strategic workforce planning, and improving profitability. We aim to make our articles informative and educational.


5 Ways to Use Data Analytics to Boost Your Bottom Line

Big data and data analytics are two of the hottest topics out there today. They come with promises of delivering business insights and high returns, but they also come with challenges for those new to the field. As a consultant in analytics, the most popular comment I receive from companies is, “we have so much data but we don’t know what we should be analyzing.” This article will provide business leaders with several tips on where to apply data analytics in order to impact the bottom line. The key thing to remember is that the value of analytics is not in the data. It’s in what you do with that data to make better business decisions or solve business challenges.

Tip #1: Use analytics to reduce your physical inventory

If you provide physical products to your customers, you undoubtedly stock inventory. From a financial point of view, inventory ties up cash and prevents you from using it for other company initiatives. If you can reduce your inventory, you can free up cash and that represents real dollars that make it to the bottom line of your financial statements.

By studying customer ordering patterns over time, data analytics can be used to help you determine how much inventory you should stock of each product. The data can show you how many of each product customers order each month and how stable that order level is over time. Analytics can determine which products are “high runners,” which products have stable order patterns and which ones are highly volatile in terms of order quantities. As a real example, in one manufacturing company, we determined that roughly one third of the products they offered were only ordered once a year, yet they were carrying inventory for all products. 

Analytics in this case allows you to decide which products to carry and how many of each. It helps you balance your desire for minimizing inventory without too much risk of running out of stock to fill customer orders.

Tip #2: Use analytics to get rid of dead product offerings

As a company grows, often its list of product offerings grows too. Product teams are very good at spending their time on the creation of “the next great thing,” but rarely is anyone dedicating sufficient time to analyzing the entire portfolio. Products have a life cycle and that life cycle needs to be managed.

Product analytics is an area of data analysis which will help companies focus their efforts on the products that generate the majority of their profit. A simple analysis of each product’s overall contribution to total profit will do the trick. This contribution is a product of the profit margin for each product combined with the volume of product that is ordered. Analytics can show you which products are growing your bottom line, which are tapering off and which ones are costing you more to manage than the profit they generate.

Tip #3: Use analytics to set your customer service levels

The focus of most companies is to grow the number of customers. However, over time the value of each customer changes. Your most important customers five years ago may not be the most important today. This is where data analytics can step in and help you make some tough decisions regarding customers and customer support.

In the previous tip, we analyzed our products in terms of which ones contributed the most to our profit. We can do the exact same analysis on our customers. In most cases, the majority of your profit comes from a few, valuable customers. As we look at a list of customers in descending order of profit, we will start to reach those customers that are contributing very little to the bottom line.

But they are still providing us with profit, right? Not necessarily. We need to consider how much time and effort we are spending supporting and managing those customer accounts. Are they providing enough profit that they are worth the cost of continued support?

Tip #4: Use analytics to improve quality and customer service

Whether you are an organization that provides products, services or a combination of the two, quality and customer service are what will distinguish your company from your competition. These two topics go hand in hand and can make or break your reputation quickly.

When it comes to product quality, no customer wants to make a purchase and find out that the product was defective or didn’t live up to its estimated lifetime. When it comes to services, no-one wants to purchase your service and be disappointed by what they received. Products and services can disappoint your customers in many ways and often the method of reporting that disappointment is an email or phone call to the seller. While the quantity of phone calls is sometimes tracked, rarely is the reason for the phone call documented. This is where analytics can provide value.

If you track your customer complaints, you can begin to categorize the types of complaints to see which ones occur most frequently. For each type of complaint, you can assess the level of impact that complaint has to your bottom line. By putting these two pieces of data together, you can determine which complaint types you should address first in order to raise your customer service reputation as quickly as possible.

Tip #5: Use analytics to focus your efforts in human resources

Human resources (HR) is viewed as a cost center, providing services to employees throughout the company. In recent years, this department has been transitioning from being a tactical team to providing more strategic projects and services. Analytics is a new service inside HR which can be used to focus the efforts of HR employees.

As an example, the old approach to HR would be to assign resources to investigate turnover in all areas of the company. With analytics, HR teams can now identify the smaller “pockets” of high turnover and focus their resources accordingly. As another example, HR teams can use data analytics to measure the effectiveness of their recruitment activities. Which recruitment channels delivered high-performing employees? Which universities or colleges delivered high-performing new graduates? In these cases, companies can save money by reducing the number of channels they use for recruiting and focus on the ones that deliver the right employees.

I could list dozens of examples of how to apply analytics inside HR, but I’ll leave you with one more. Consider the cost of training your employees. How do you know that the training was worth the money you paid? Data analytics can help you answer that question.

Data analytics is an immensely valuable tool to assist companies in making better decisions in virtually any area of the organization. Whether it’s managing inventory, product lines, customer accounts or workforce challenges, the application of data analytics to drive business decisions has become a must-have skill. Without this skill, companies will find themselves at a competitive disadvantage and on the road to obsolescence.

Not sure how to get started with analytics? Both Coursera and EdX provide a wide selection of free, online classes available to everyone. You don’t need to be a math expert to learn how to apply analytics to your business. You can always find the analytical help that you need outside of your company. You only need to understand the benefits and the possible applications to your own business. Start the journey and find the skills you need as you move down the road of analytics maturity.

Tracey Smith is an internationally recognized business author, speaker and analytics consultant. She is the author of multiple books and hundreds of articles. Tracey has worked with and advised organizations, both well-known and little-known, on how to use data analytics to impact the bottom line. If you would like to learn more, please visit  or contact Tracey Smith through LinkedIn. You can check out her books on her Amazon Author Page.