Analytics to Drive Business Efficiencies (ClaytonMcKervey)
TechnologyMarch 12, 2020 - Clayton & McKervey PC
This is a thought leadership article from PrimeGlobal member firm Clayton & McKervey in which they investigate the importance of properly collecting and analysing data.
Investment in data analytics programs remains on an upswing as more businesses discover the benefits to uncovering trends, hidden patterns and correlations that would otherwise remain buried in a huge amount of raw information.
According to Clayton & McKervey senior manager Ben Smith, ensuring a company is properly collecting and analyzing data is essential to reducing waste and improving operations, and could result inupgrading production equipment, focusing on employee training, or revisiting the sales and account management process.
“Drilling down on results to better understand what is working for a company and where changes need to be made is an easier task for those with data measuring processes, procedures, inputs and outputs. For those with little or no data, those opportunities are more difficult to determine. That’s why analytical software tools are becoming increasingly important to reveal helpful insights, which allow companies to make decisions based on this information—information that often gives them a competitive advantage.” Ben Smith, Senior Manager - Consultancy, Clayton & McKervey
Because the type of data collected can provide information on various processes, it’s important to select the right data analytics approach to meet the company’s experience, ability and goals. Here are four ways companies can do this:
1. With Descriptive Analytics:
Using data to describe what happened over a specified period of time. Any data collected is specifically meant to help management discover what happened. Have the number of sales for a new product increased? Is the company selling more in foreign markets?
2. With Diagnostic Analytics:
Seeking to answer why something happened. This process involves the collection and analysis of several data components across various points in the supply, production or sales process. Did slower delivery times impact sales? How did the latest marketing campaign impact sales? It also requires hypothesizing.
3. With Predictive Analytics:
Focuses on determining what is going to happen in the coming months. This also involves the collection of several data points but requires a more rigorous analysis of multiple variables to understand how they impact a specific outcome. How do changing weather conditions impact sales? If they do, how do we manage production to meet sales demand?
4. With Prescriptive Analytics:
Addressing actionable items on what a company believes is going to happen. For example, if it’s likely that a cold winter is coming based on an analysis of six weather models, then should the company order more supplies to boost winter production?
There is a four-prong process that companies need to work through to get the most out of their data analytics:
Prior to starting a data analytics program, it’s necessary to bring definition to the process to ensure business goals and objectives are in alignment with the type and amount of data being collected. Define immediate, short- and long-term goals and review data to ensure relevant information is being captured. Do not to collect data simply to have it, and if the data is not obtainable, build a process to capture it.
Before beginning data collection, select the right software tool to manage the process. There are a number of packages available that fall into several categories such as tagging, analytics, visualization and more. Depending on the framework established in step one, the best tool is one that supports the internal team and allows for the collection and analysis of data from various sources.
Recording data alone will not provide the actionable steps the process is designed to offer. Most companies will need to work with a data storyteller to review the data and identify anomalies, trends, relationships and changes. It’s also important to bring in various perspectives, as subject matter experts may have different interpretations due to their business knowledge. However, their involvement often generates an additional dimension to the results.
Once the analysis is complete, management will need to review the information to decide what changes need to be made. For many, it can lead to deeper insights and observations about a process or opportunity, while others may embark upon a new strategic initiative. Since the action step is based on the data collected and analyzed, it’s important to ensure the prior three steps are properly followed. It’s almost impossible to make decisions about what to change if there is inadequate collection or analysis.
“The value of a data analytics program cannot be understated. The keys are to spend time in the set-up and work closely with stakeholders to find the right tools. Because this pursuit can be complex, companies are encouraged to turn to an experienced provider to help guide them through the data analytics process.” Ben Smith, Senior Manager - Consultancy, Clayton & McKervey
Clayton & McKervey PC
Headquartered near the international border of the U.S. and Canada, Clayton & McKervey is a Detroit-based, full-service accounting and business advisory firm focused on global business. The firm’s clientele includes closely held, middle-market, growth-oriented companies. Since 1953, Clayton & McKervey has created a strong reputation, both domestically and internationally, with four types of clients, U.S. entities with operations in other countries, foreign entities expanding to the U.S., businesses with international growth plans and clients in need of transfer pricing service.Learn more