This is how AI is changing business expansion
What is the value of millions of data points if organizations do not know how to act on them?
The key is not collecting more information, but turning it into decisions that anticipate the future.
There was a time when data was simply a collection of numbers stored in systems, with no clear story behind it. Today, the same data can define the direction of a company… or leave it behind if it is not interpreted in time.
For years, organizations have faced the challenge of collecting and making sense of multiple streams of information coming from a wide variety of sources on a constant basis. Sales figures, purchasing trends, consumption peaks, or demand drops are all pieces of the same puzzle that, with the right analytical strategy, can become key insights for decision-making.
Data and decisions.
In today’s context, having data available is not enough. The market tends to favor those who can understand where, how, and when to act. The question is how to turn that information into a truly useful tool to gain differentiation in a competitive environment.
According to the third edition of the Business Challenges survey by EY Shape the future with confidence, in Colombia 90% of companies consider artificial intelligence (AI) an important factor, especially in analytics and Big Data, referring to it as “the “backbone” of all digital transformation.”
In the same line, Deiro Nicanor Gonzalez, Technology Manager at Esri Colombia, explains:
“AI reduces time and errors by automating data preparation, improving quality, and supporting analysis by detecting anomalies, patterns, and trends early, which accelerates decision-making.”
Tasks such as data engineering, which previously could consume more than half of an analyst’s time, can now be completed in hours with a lower margin of error.
However, adoption is still partial. According to the IDC LATAM report, only “47% of organizations in LATAM use AI. Of those companies, 60% use these solutions for BI and analytics as part of a business strategy.”
AI adoption.
In Colombia, a significant portion of the market remains focused on descriptive analytics. The use of AI for more advanced approaches, such as predictive (what will happen) or prescriptive (what should be done) models, is still limited, representing an opportunity for organizational evolution.
While some companies still rely on spreadsheets, others have migrated to business intelligence (BI) tools, which allow them to diagnose the state of an organization through key performance indicators (KPIs) based on historical data.
Business analytics (BA), on the other hand, goes a step further: it seeks to anticipate future scenarios and answer questions such as “what if…?”, using advanced statistics and AI models. This approach enables deeper pattern recognition, decision simulation, and more accurate root-cause analysis.
In simple terms, BI acts as the business rearview mirror and dashboard, while BA resembles a GPS that guides the best route toward a goal.
“BA ends up being better because it means the organization is evolving in terms of analytics. But BA does not replace BI; both are business analytical practices tied to an organization’s maturity.”
says the Technology Manager at Esri Colombia.
From BI to BA.
Beyond traditional analysis, the geographic component is increasingly playing a key role in decision-making. Questions such as where the highest commercial demand is, whether a sales network is cannibalizing itself, or which areas have real potential can be answered more precisely through spatial analysis in Geographic Information Systems (GIS).
Nicanor explains that tools such as ArcGIS from Esri:
“Enable BI and BA to be enriched by incorporating the geographic component, helping organizations understand not only what is happening in the business, but where it is happening. Its geospatial analysis capabilities and integrated artificial intelligence enable the detection of patterns, anomalies, and territorial behaviors, accelerating decision-making and improving strategy and operations.”
The integration of the geographic component into BI, known as location intelligence, allows KPIs to be placed in a territorial context, enabling decisions based on location. In BA, geospatial analysis helps project future scenarios by considering business behavior across different areas.
Geographic intelligence.
Although for years this type of intelligence was reserved for highly specialized profiles, it has now become more accessible to organizations seeking to incorporate a territorial perspective into their expansion and commercial strategy decisions.
|
|
