To address resource constraints, PIPC adopted Tableau Desktop and Tableau Server.
In Tableau Desktop, analysts can easily recreate analyses for customers instead of starting from scratch with every new request. Analysts leverage R in Tableau, pulling data from Microsoft Access, SQL Server, and Excel. With Tableau Server, PIPC shares data with customers in a secure environment.
Increasing data quality with visual analytics ultimately helped increase productivity among PIPC employees. For an average of 15 reports, this process reduced reporting time from 12 hours to 5 minutes. With Tableau, PIPC has streamlined their workflow, with more room to explore new ideas and test hypotheses with a few clicks.
Increased demand, limited resources
In 2013, the number of patent applications around the world was 2,568,000. In the same year, Korea was ranked as the world's number one in resident patent applications per GDP $100 billion and per million population. A core element that drives a company’s valuation is its intellectual property rights. In research and development, companies collect technical data of similar or competing products and analyze domestic and overseas patent information. As important business decisions hang on these analyses, accuracy is crucial.
Patent Information Promotion Center (PIPC) is a public organization that provides patent information and supports policies of the Korean Intellectual Property Office. PIPC’s consulting division analyzes patent data to guide their customers in the right direction. As part of this process, PIPC researches worldwide patent documentation to help the customer understand the competitive landscape and important statistics related to the customer’s specific technology.
For existing data, PIPC's analysts used Excel for both analysis and visualization—an incredibly manual, time-consuming process. It took at least half a day to create 10 to 15 reports and up to a day to distribute the final versions. And each new request required analysts to once again cycle through the manual process.
Acquiring data was increasingly difficult—making it harder to produce high-quality reports for customers. PIPC’s standard process couldn't meet ever-increasing customer needs for higher-quality, deeper statistical analyses. With restricted IT resources, PIPC needed a self-service solution built on governed data. And they needed to be able to securely share this data across the company.
In addition, PIPC’s consulting division wanted to work more collaboratively with customers around patent consulting reports. To enhance customers’ understanding, PIPC needed to make their analysis reports more intuitive with visual analytics. To address this challenge, PIPC started to search for a new approach to analysis.