The Whole Is in the Part: Correlating Events to Support Results

A few days ago, I was asked what, from my experience, I could share on relevant topics in technology that are on the rise. 

I must admit that I had doubts because there are many possibilities. On the other hand, a topic that I have perceived to be evolving in the discussions in which I participate is the challenge that organizations have experienced in adopting initiatives aimed at analytical culture in business strategies. 

This is not an easy task as it requires an assertive leadership capable of performing and connecting different perspectives, intersections, variables and characteristics that produce tangible results for the business. 

A recent study that analyzed evidence on the importance of data in large corporations, conducted by New Advantage (2023), indicated that the progress of organizations in building a data-driven business culture is slow, according to leaders of large companies. 

Among the surveyed companies, only 20.6% reported developing a data culture, while 39.5% believe in data management as a business asset.

This is because data are collected in all organizations, even if not all are analyzed. A study prepared by Gartner explains and indicates an analytical maturity model for companies, showing the stages of evolution in the use of data in organizations – descriptive, diagnostic, predictive and prescriptive analysis.

For this reason, I believe that the work of spokespersons of organizations, in the technological scenario, is fundamental to make the teams aware of the importance of using the data generated within the companies themselves as a means to create more strategic processes. 

Predictive Analytics as Part of a Culture of Care – and Prevention 

Among the stages of the analytical perspective, predictive analysis is translated into a moment that is extremely desired by companies, involving understanding what could happen and supporting the culture of prevention. When combined with prescriptive analysis, it provides an understanding of the best ways and alternatives for the prevention of certain scenarios. 

In my last article, I shared a few ideas about the importance of a culture of prevention in organizations, which – by the way – is on the rise, as well as the evolution of predictive analytics. As a survey released in 2023 by Zion Market Research shows, the predictive analytics market could reach revenues of approximately US$39.1 billion by 2028.

Looking at the analytical maturity model in organizations is also understanding that it includes different processes that require support, in addition to the critical capacity of different resources and available technologies. 

The challenge of embracing the analytical culture that I mentioned at the beginning of this article made me look for resources that I believe to be appropriate to support this process, within my area of activity, which is data monitoring. On that topic, we must first understand how the predictive analysis of future events works based on data.

Correlating Events and Finding New Perspectives

From a predictive analysis based on the data that is monitored in a business, in addition to the facts found in the operation of a company, it is possible to correlate events and understand which parts of the whole have the largest incidence of situations that cause discomfort, financial losses or even systemic stops in the organization. 

It is at this moment that three fundamental monitoring elements emerge: symptom, cause and consequence. Understanding how events are correlated based on the metrics we collect gives us knowledge about these mentioned elements, which can lead to an interruption of services or a break in the production chain, preventing unpleasant surprises. 

An exercise that I really like to exemplify this topic is analyzing the e-commerce segment. The Hot Sale period in Mexico, an annual event that boosts e-commerce sales, that took place between May 29 and June 6, 2023, recorded more than 11 million purchase orders, according to data provided by the Mexican Association of Online Sales (AMVO). The campaign resulted in almost MX$30 million(US$1.8 million) in sales. 

For these sales to take place, a series of elements must be considered, from the buyer’s experience when accessing the website, to the payment system, sales processing time, number of purchases generated, and website availability, among others. 

For example, in a scenario of unavailability of an e-commerce platform — known as downtime — businesses are paralyzed, which generates large financial losses. 

Financial loss is a consequence. The downtime of the website, a cause. Now, I need to understand the symptoms that led to the cause and the consequence. 

The symptoms are diverse: a large volume of transactions for an infrastructure that was unprepared, a specific event in the payment system, an overload in the system as a whole. Furthermore, the symptoms can appear internally or in third-party systems, but they must be understood as parts of a whole – the unavailability of e-commerce.

Many metrics are analyzed to arrive at a fact. The relationship and analysis of different metrics, coming from several pillars and environments, will allow a decision-maker to guide a more assertive workflow and strategies, thus avoiding unwanted consequences.

Joining Forces for a Preventive, Proactive Culture

As I mentioned, monitoring cannot be based on a single metric to understand the events that take place, at the risk of resulting in a poor analysis and potentially wrong decision. 

In this sense, the correlation of events becomes an ally to strategic monitoring and predictive analysis.

Very often, we fail to encourage a more proactive culture, regarding the analytical perspective, because we work in a fragmented way, without communication – or “communicACTION” – between the IT team and other areas. A point to highlight is the fact that it is not enough to update the tools and rely on new functionalities or resources for strategic work when monitoring and analyzing data. It is also necessary to promote data reading, interpreting and literacy capabilities. 

In summary, it is necessary to monitor different data and be strategic in correlating events. Exercising critical and analytical thinking drives solutions and results.