Data, Data, Everywhere!

A tale of turning bureaucracy and inefficiency into a data-driven machine

Once upon a time…

there was a large distributed retail organization. They had over 250 locations. Almost all of these independently run centers had been businesses that were acquired by the company over many years.

Every day…

each location provided services to many consumers. Although corporate was trying to centralize some operations, for the most part, each center managed its operations, prospecting, and staff recruitment.

One day…

the company realized its operations were inefficient and costly. They had added many people to the corporate office whose jobs were to collect and summarize data from each center. Worse, each location around the country spent a significant amount of time every week just trying to deliver data back to the corporate office. The data often arrived too late to be useful. Besides, the company had data in 30 different databases, and many excel spreadsheets hidden in peoples’ computers.

Because of that…

we suggested a new approach. What if we could streamline, standardize, and automate the data collection process? We could also collect and normalize all of the data into one centralized location for real-time dashboards and better decision-making.

And because of that…

we implemented a cloud-based data warehouse with an Integration Platform as a Service (iPaaS) solution to collect the data. We knew that the solution we delivered would have to be cost-effective and straightforward to maintain and change. We chose Microsoft’s Azure Cloud SQL for the data warehouse and Dell Boomi for the integration solution because of their simplicity, price, and stability. 

Until finally…

data started to flow from all parts of the organization into one centralized bank. Prospecting data from the CRM, customer information from the customer management system, support information from the call center, and even data from google sheets and excel spreadsheets all flowed into a single data warehouse. With all of the data in one place, we could begin to create the straightforward dashboards the company needed to make decisions.

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