As a mathematician, I've always been a fan of data analytics, and big data. And I have always looked to used it to drive operational performance improvement in every company I have worked in going back to the 80's.. The Edward Demming quote 'In God we trust, everyone else bring data" is one of my favourites, and it's a mantra that I look to live by, as can tell us so much.
The challenge with all of this is not how do I gather the data, how do we structure it, or which tools will we use to analyze it, but what are the questions we are looking to solve.
Just recently I had the opportunity to talk with Michael Chapin, CEO of leading e-commerce floral company, From You Flowers, who has made analytics central to how he runs his business. Michael decided that rather than outsource or bring in external consultants to run their analytics they would build an in-house team. The recruited some Ivy League graduates, and then set them to lose on over ten years worth of historical data to try and find opportunities to give them an edge in this highly competitive business.
There were no sacred cows, Michael insisted every part of the business was available for optimization.
The results have been amazing. Prior to using analytics, Michaels business was successful, growing by 10% every year from 2002 to 2011. Since the introduction of the in-house analytics team, the business growth has risen to 30% year on year for the last five years.
Here are seven areas where they have used analytics to transform their performance which boosted revenue, increased profits, and improved customer satisfaction and retention.
When it comes to delivering flowers, From You Flowers uses a network of florists to fulfill orders, as well as their own distribution centers. Analytics has allowed them to predict their ability to meet customer demands, which are often for same day delivery, by understanding the impact of traffic patterns and average delivery times for each supplier in major cities. This allows them to make and meet commitments, or pass on business where they know that delivery is not possible, or to propose a next day delivery.
Florist performance can vary based on many factors, such as time of day, the day of the week, or the product being sold, etc. Analyzing supplier performance helps identify which of their many suppliers will give the highest probability of success for any give orders based on location, which increases their order fulfillment.
