When Preparing Data Stops Stealing Time from Analysis

Automatización con IA

Areas

Herramientas de automatización. Data-driven decision-making. Inteligencia Artificial. Marketing automation. Employee experience

There is a recurring problem in very different organizations. Teams working with data spend a disproportionate amount of their time doing the same thing: collecting, merging, cleaning, and formatting information before they can analyze it. The real value work comes at the end, when there is little time left and energy is already spent.

We have accompanied two organizations, in different sectors and contexts, that arrived with the same diagnosis. In both cases, the solution was not a change of tool or a process consultancy. It was to build a custom digital product that automated the data flow from start to finish.

An insurance company: frictionless Employee Experience reports

A large insurance company conducted periodic Employee Experience surveys with thousands of employees. The data came raw from a survey platform. From there, a team had to process that information, merge it with different organizational perimeters, and generate presentations in PPTX and PDF format for different levels of the company.

The process was manual, repetitive, and prone to errors. Each report cycle consumed days of work. The final version arrived late and with a margin of error that no one wanted to assume.

We designed and developed an internal web application that connects directly to the data source via GraphQL, applies the business rules of each type of report, and generates the output files in PPTX and PDF with all printing specifications included: crop marks, color profiles, bleeds. The team selects the type of report, the organizational perimeter, and the year. The application generates the document in seconds.

The development included 95% test coverage, achieved with the support of artificial intelligence. This ensures that each system update does not introduce errors into the report logic.

The result is a drastic reduction in preparation time and a report cycle that is now measured in minutes.

A leading educational institution: real visibility on the marketing budget

The Performance Marketing team of an educational institution managed active campaigns on Google, Meta, LinkedIn, and Display. Budget tracking and the performance of each campaign were done on spreadsheets that someone updated manually, connecting data from different platforms.

The process took hours. The data was never entirely up to date. Making investment decisions required waiting for someone to finish reconciling the numbers.

We built a web application that integrates the APIs of all advertising platforms via OAuth, centralizes the data in a single dashboard, and allows the team to synchronize all information with a single click. The application includes an MCC-type panel that groups all active clients or programs, automatically detects deviations from the target, and exports the data to Google Sheets in real-time.

What started as a script in Excel evolved into a proprietary product, with scalable architecture and accessible from any browser.

The team regained the time previously spent consolidating data and invested it in optimizing campaigns.

What these two projects have in common

Both clients came with the same problem described in different ways. In both cases, the solution involved analyzing the real workflow, identifying where time was lost, and building a tool that automated it without removing the team's control.

We provided product criteria, technical architecture, and development capability. The result was not a generic tool adapted for use, but a product designed for that specific workflow, with business logic incorporated and the user experience designed for those who use it every day.

When data flows on its own, the team can focus on what matters.

Does your team also spend time preparing data before you can use it? Tell us how you work and we'll explore what can be automated.

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