Difficulty deciphering large volumes of data
Intellipharm’s pharmacy customers capture large amounts of data, on everything from minute operative details to product sales, revenue, stock levels, periodic updates on turnover and more. This information comes flooding into Intellipharm’s database on a daily basis. Needless to say, packaging it up in a user friendly format was a real challenge. “We work with over two million rows of data every single day. The sheer magnitude can be overwhelming if not dealt with efficiently,” said Leny. “We always strive to present customers with their information as soon as possible, so they can immediately implement the insights from their sales data, however, it was taking two to three weeks to create customised dashboards. In the fast-paced world of sales, data can become completely redundant within three weeks.” The company was using web technologies to interact with the huge quantity of data, which proved incredibly time consuming. As Intellipharm continued to grow, it was simply not feasible for the business and its customers, who rely on the business intelligence provider for real-time information, to continue with the web technologies. “In pharmaceuticals, a hay fever medicine becomes obsolete when the pollen settles. Seasons and trends can change in a matter of days. The last thing we wanted to do was present stale information to our customers,” Leny said. Web technologies like PHP were also difficult to drill down. In fact, Leny was the only team member able to interact with Intellipharm’s data using the unfriendly web technology system. Data reaches Intellipharm’s database from thousands of sources in various formats. From there, the web technology system was slow in converting the data into one efficient flow of information, delaying the speed to action for customers. “We were meeting barriers throughout the process which meant our customers had to wait longer for insights. We recognised this delay and even created a new business unit to speed up our response time,” Leny said. Despite this change, Leny was still pressed for time, sieving though two billion rows of information to present blended data insights. “We could typically present a report to our customers on one data set – their revenue or stock for example – but not how each set affected the others,” said Leny. “We were looking to create reports that showed customers how every facet of their data could reveal an entire business story. We wanted to give them that ‘ah-ha!’ moment when they realise the cause and effect of business operations.” Intellipharm needed a system that allowed its team to pull a customised report encompassing multiple data sets so customers could view the entirety of their data. Web technologies simply weren’t allowing data sets to speak to one another. “We were sure there was a goldmine hidden within the static database system just waiting to be analysed,” said Leny.