Customer Frustration
A common issue in today's ultra connected world is having too much data.
And then that data sits in many different places in different formats all across the enterprise.
This was exactly the problem that a consumer product company faced when we started working together.
The over abundance of data was making it difficult to focus the company on the right metrics. And department heads and other teams had gotten too comfortable with “their” data and did not want to make changes.
Data can be one of the biggest obstacles to implementing a successful AI program.
The Problem
Too much data prevented a consumer product manufacturer from clearly understanding the state of their sales and distribution landscape in real time.
The Solution
The first step to a solution is admitting that you have a problem. You must also find and track every data source.
In addition to having their favored data, teams had created their own reporting and data storage solutions after becoming frustrated with the existing archaic process.
Creating a data lake that could serve as the definitive source of any data would also allow for added security, speed of retrieval, and common formatting.
Once the data infrastructure was set, then a layered approach to implementing an AI system that could analyze information and write a number of different reports was brought online.
The flexible system allowed teams to generate a number of reports and even new ones that could provide new insights.
The time it takes to produce reports has been cut from an average of seven business days to several hours.
The new efficient reporting system also allowed business analysts to move into higher level work and not just crunch numbers. But understanding some of the drivers of business results.