Unlock operational excellence through data

Introduction 

The application of data analytics to inform process optimization and enhancement decisions has become a key focus of many organizations in recent years. This has been evidenced in recent research from PEX Network, with The PEX Report 2022: Global state of process excellence finding that data analytics will be the greatest focus for investment in 2022, according to 43 percent of those surveyed.

With many realizing the benefits that can be attained through an advanced data analytics strategy, such as improved process visibility and the opportunity to personalize and enhance customer experiences, it comes as no surprise that organizations are looking to perfect the application of data analytics.

In light of the increasing popularity of data analytics initiatives, this PEX Network guide analyzes the state of the field of analytics, highlighting the key challenges that organizations face before diving into the benefits offered by an optimized data strategy.

Drawing on insights from companies including General Mills, Minitab and FastPeopleSearch, this guide offers advice on how to get the most out of business analytics for those looking to begin their own data journey on the path toward operational excellence.

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Data and analytics investment is increasing

With businesses across the globe realizing the power of advanced data analytics, the implementation of technologies and strategies for the advancement of data practices, such as automated accounts reporting or analytical dashboards, has been increasing rapidly.

One potential cause of this advanced rate of adoption is the increasing availability of data and the variety of sources that it is drawn from. The majority of tools and technologies that are applied in the quest for process excellence that include chatbots or online registration and subscription forms, are capable of collecting data in one form or another. This means organizations now have a plethora of data sets that can be analyzed in attempts to gain visibility over their processes and learn how to optimize them.

Sally Stevens, co-founder of people-focused search engine FastPeopleSearch, believes that this widespread availability of data means that organizations will no longer gain their competitive edge from the size of their database, but rather from their ability to analyze it effectively.

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“There is a lot more data and information readily available to businesses, which makes it easier for them to take advantage of it,” she notes. “A lot of the competitive edge will now come from how good companies are at analyzing and understanding their customers’ needs and wants [through data analytics].”

This rate of adoption has been accelerated by the continuous development of new technologies that make data analytics not only easier and more effective, but also more accessible, according to Jennifer Atlas, global marketing development manager at data analytics platform provider Minitab.

“The [progression of] technology has been enabling people to suddenly join in with data analytics and work on it in a way that was only in the realm of someone with a data-related degree,” she explains. “Today, anyone who has any interest in exploring data can really get some great insights, as long as they use the right tools.”

With data now so readily available, organizations have never been in a better position to begin, or advance, their journey toward an optimized data strategy and operational excellence. The next section of this guide delves into the key benefits that organizations can enjoy if they are able to achieve an optimized data strategy.

The primary benefits of an optimized data strategy

Data analytics has been used for driving operational excellence in recent years, but companies may not fully understand how best to leverage it to experience the many benefits it can provide.

According to Minitab’s Atlas, an optimized data strategy can support multiple goals, including reducing costs, accelerating growth or improving return on investment (ROI) for business initiatives.

Using data to discover insights either in a process or customer behavior supports actions to create value and using it again to prove ROI on initiatives can help not only impact results but improve a company’s culture, “particularly with regard to initiatives that challenge the status quo and seek to change the standard best practice in an organization”.

“We have seen organizations who have embraced analytics and were able to mobilize projects with much less friction – analyzing their results and demonstrating ROI using their data enabled them to gain momentum for additional value-creating projects,” Atlas remarks. “Overall, leveraging their data not only resulted in improvements in profitability, but actually made a significant positive impact on their ability to compete in the marketplace.”

Data can help easily evidence ROI in real time through advanced analytics platforms, allowing businesses to continuously monitor and improve processes and initiatives to accelerate the journey toward operational excellence.

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With organizations now collecting large amounts of data from a wide array of sources, maintaining clarity of what data companies possess and what it tells them about their operational excellence goals is no simple task. According to Sabin Pradhan, senior data scientist at multinational food manufacturer General Mills, attaining this clarity is one of the main advantages offered by an optimized data strategy.

“It allows organizations to designate data domain experts,” Pradhan explains. “This not only helps in understanding what data companies possess and how it is all connected, but also how they can leverage that data to create continuous business value.”

This increased visibility over how processes are operating informs business leaders of areas where steps can be taken to advance the drive for operational excellence. Data clarity is also a key requirement for applying data analytics in the most effective way and getting the most out of the data, which the next section of this guide looks at.

How to get the most out of the data

True data analysis is about more than just the implementation of business intelligence initiatives like data mining or calculating averages and trends based on data sets. Although these are great places to start, there is much more to be achieved when businesses truly get to grips with their data.

Joshua Zable, chief marketing and strategic planning officer at Minitab commented: “Put simply, if you are doing the same simple analyses as everyone else, how do you expect to get an edge on your competition?”

FastPeopleSearch’s Stevens explains that the first step of any attempt to apply advanced analytics should be to set reasonable goals for how the data will be utilized.

“Businesses need to set goals for what they want to achieve”, Stevens notes. “Once they have those goals, they can start searching for data that will help them. It is also important to research the type of data necessary for the task at hand and which analytics tools can help reach their goals.”

With a plethora of data services and platforms available for businesses to choose from, such as real-time analytical or process mining dashboards, deciding on the correct tool for the job and applying it correctly can be difficult and represents a potential spanner in the works for operational excellence initiatives.

Pareto charts

A Pareto chart is quite similar to a traditional bar chart, however, it goes a step further by indicating the frequency of defects in data sets, along with their cumulative impact. This is important from a quality improvement perspective, as it allows organizations to identify the most critical quality issues based on various factors such as volume or expense.

Boxplot analysis

Boxplot analysis takes the calculation and display of averages to a more advanced level. This type of analysis not only presents the central value, or the median, but also displays the level of variance associated with each of those central values. This is useful because it provides a visual summary of data, enabling speedy identification of mean values, central tendency and variability.

Predictive analytics

Predictive analytics is the application of analytical tools such as regression analysis, predictive modelling or machine learning to make predictions about how a data set will progress in the future. This allows organizations to make informed decisions and plan ahead, proactively implementing initiatives to counter a predicted problem or further the organization’s goal of operational excellence.

By implementing a solid data management strategy that utilizes the advanced analytical tools mentioned in this guide, organizations can gain an understanding of not only where operational excellence is lacking, but how to rectify this.

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Advanced data analytics in action

Zable offers an example of how the tools mentioned in this section can be applied in a real-world environment to drive operational excellence in a business.

Zable shares a story of a business owner who was applying analytics to the management of a New York bar, but was only really looking at mean values for certain points in time. The company’s data strategy was not sufficient to counter long wait times that customers were experiencing.

After entering the business’s data into the Minitab analytical platform, it generated a Pareto chart, which identified the busiest days and which had the greatest impact on the bar’s success. Following this, a boxplot analysis was applied; while the bar owner had correctly calculated the mean and median of 300 drinks per hour, there were several time periods where they would exceed this significantly, sometimes going up closer to 500, almost double than what the mean suggested.

Finally, Zable ran a regression analysis to offer predictions for how many drinks could be expected to be ordered at certain time periods. Using this information, the bar was able to make slight adjustments to the working hours of bartenders in anticipation of the busiest periods, effectively reducing the longest waiting times that customers experienced.

Conclusion

This PEX Network guide has discussed the current state of data analytics investment and offered some potential explanations for increasing investment. Through analysis of traditional data practices, the guide has observed that many organizations may be unaware of the true value that lies in organizational data and how to unlock that value.

Some of the major advantages that can be gained by optimizing data strategies in the quest for operational excellence include reducing costs, accelerating growth and demonstrating ROI for projects, which has traditionally been difficult to achieve. Attaining clarity over the data businesses possess helps organizations to understand where the greatest opportunities to drive operational excellence lie.

In order to move past traditional analytics and take organizational understanding of data to the next level, businesses will need to adopt advanced analytical tools that do much more than just calculating averages. Organizations can leverage Pareto charts, boxplot analysis and predictive analytics to identify defects, understand variance and make predictions about the future progression of data sets.

Those who recognize the true value that can be attained through data analytics will have a much easier time driving operational excellence than those who do not. Organizations that understand the true value their data holds have already taken the first step toward achieving operational excellence.

This report was originally published on 03 November 2021 and was updated on 07 October 2022