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Numerical Insights publishes articles on a variety of topics including data analysis, data visualizations tools, improving business results, supply chain analytics, HR Analytics, gaining competitive advantage, strategic workforce planning, and improving the bottom line. Feel free to browse our topics below.

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How to Impress your Leadership with Practical Analytics

Conducting analytical studies in business can involve the use of many mathematical techniques. Some of these techniques are statistical in nature and some are closer to arithmetic approaches. Believe it or not, you can yield a great deal of value without having to spend 100% of your time in advanced mathematics.

Since most of my followers are interested in more than just HR Analytics, this article will present practical examples of using analytics to make a difference in many areas of a company.

As you follow various experts in analytics, you will soon learn their views. I tend to be referred to as a down-to-earth, call-it-like-it-is, practical business person. It is not unusual for me to receive emails and comments thanking me for “being real” or referencing me a contrarian. If it is contrarian to help steer people away from zero-value, pie-in-the-sky studies and toward what a business really needs, then I am happy to be a contrarian.

Now, let’s get straight to it. Here are a few examples of practical uses of business analytics that are certain to please your leadership. (Note: If you’re a new analytics team, you have roughly two years to show value before most leadership teams “re-evaluate your worth.”)

Show Me the Money

There are several ways that analytics professionals can produce “real money” from analytics…and you don’t need data as large as Amazon’s to do it. Think about two categories of money inside a company. There is the money that comes in from sales and there is the money tied up in various places in the company.

On the “sales side” of money, analytics can help you predict whether each of your sales people will hit their targets, which types of customers are interested in which types of products and what your future sales will likely be. Forecasting capabilities of future sales can be quite complex when you try to examine past performance combined with a mixture of industry market forecasts. Forecasting almost certainly becomes a combination of both math and judgement. In recent years, I developed a forecast for a manufacturing company that served many industries. Some of those industries were forecast to go up 20% while at least one other was forecast to drop by 40%. Looking at the company mix of industries certainly forced us to make tough decisions about how we would use the industry forecasts in combination with historical sales data.

On the other side of money, the side where money is tied up in the company, purchasing is the easiest example I can give you. When your purchasing team or individual buys the items that your company needs, it ties up money in inventory. When that money is tied up, it cannot be used for anything else. The art of managing inventory lies in the mathematics of forecasting inventory needs so you neither run out nor leave excess inventory lying idle on your shelves.

Also in the purchasing area of your company is the ability to use data analysis to analyze where you spend your money and on which categories of products. Often in larger companies, there are opportunities to “consolidate spend” for cost savings.

Optimize My Profit Contribution

The products or services a company sells have a life cycle. When products are in demand and are unique, a company can invoke a large profit margin on them. As time goes by, most products tend to become obsolete, popularity of the product fades or an increase in competitors floods the market with too much product. In these cases, the profit margin begins to fade. The tough decision for companies is in when to stop making a product.

The math behind this analysis does not need to be complicated but it can be time consuming when you sell thousands of products. Examinations of margins, volumes and the cost of the workforce and processes supporting the products are good factors to take into consideration.

This product profitability analysis can also be done at the customer level. Examining the revenue, volume and historical trends of customers leads to decisions on which customers to support with high levels of customer service (dedicated sales reps) and which can be moved to lower levels of support (shared sales reps or telephone support).

Keep My RIFs out of the Courts

It happens. Business conditions change quickly and sometimes you just have to RIF. If you’re not familiar with this acronym, it stands for a reduction in force, layoff, downsizing, right-sizing, redundancy, whatever you wish to call it.

RIFs can be voluntary or involuntary. They can be done in a people-friendly way or a harsh and immediate way. Which way a company chooses to go often depends on the urgency (time available before the RIF needs to occur) and the cultural view of the organization. When there is an immediate need to reduce the cost of the workforce, there is a risk that due diligence will be forgotten in the RIF planning. By due diligence, I am referencing the mathematics required to ensure that your RIF does not impact a specific age group, gender or ethnicity.

The mathematics of RIFs is a combination of arithmetic for one method of adverse impact analysis and statistical testing for the other. Since each side of a court case argues in favour of one or the other being a more valid measurement, it is best to do your “RIF math” with both methods to ensure you won’t be invited to the courtroom.

I wrote in more detail on this topic back on May 3rd, so I won’t repeat myself here. You can use this link to read the adverse impact analysis article if desired.

Focus on What Matters

We’ve heard this said by several analytics experts but sometimes the point is missed. It’s not what matters to the analytics team. It’s what matters to your leadership and, in the case of HR analytics, what matters to your employees. If you want to truly impress your colleagues and leadership, pick your projects for the REAL value that they produce. 

Bio

Tracey Smith is an internationally recognized analytics expert, speaker and author. Her hands-on consulting approach has helped organizations learn how to use data analytics to impact the bottom line. Tracey’s career spans the areas of engineering, supply chain and human resources. She is CPSM certified through the ISM. If you would like to learn more, please visit www.numericalinsights.com or contact Tracey Smith through LinkedIn. You can check out her books on her Amazon Author Page or on Kobo.