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.
1 - Improved Service Level Performance
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.
2 - Better Order Fulfillment
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.
3 - Improved Supplier Management
Analyzing the customer complaints and refund requests allow them to drop poor performing suppliers, either from on-time or product quality perspective. Which helps to ensure that their clients get good quality flowers on time.
4 - Maximise Customer Value
When you can identify those customers, who are more likely to come back and do repeat business it allows you to optimize your marketing investment. Building long-term relationships with customers which then maximizes their value to you, and the level of repeat business.
5 - Driving Down Costs
The flower business is very seasonal with certain days, such as Valentines Day or Mothers Day, having ten times the demand as most other days. This requires a very flexible labor force. Turning the analytical focus inward has and helped to significantly improve staffing levels forecasts which helped to manage operational costs.
6 - Improved Advertizing
Every advertisement is A/B and even C split-tested. All landing pages, pop-ups, and even product images are assessed for their effectiveness with tweaks being made to ensure maximum results.
Even the positioning of products on the website is measured to identify the best location to help drive engagement and sales.
Advertising can be expensive, and it's important to know how to get the best return on investment.
7 - Better Product Management
There are literally thousands of different products that could be offered. Understanding which are the most popular products or a combination of products and this too can vary by region, and also seasonally. The data is used to ensure the company to targets the right product at the right time, which helps to increase sales.
I asked Mike what's next for his data analytics team? His answer was "A goal of ours in 2017 has been to strengthen the scale and power of our analytics back-end. We're generating several times more data today than we were just a year ago. As our customers have starting using more devices to interact with us, our overall volume of interactions has grown. As our volume of interactions grow, our volume of data also grows. Rather than aggregating, or becoming less specific with our data analysis, our analysis has become even more granular of everything from site features to ad campaigns. As our customers change the way they shop, it is our focus to use big data to change the site to create an experience that is on the forefront of online shopping."
When you take the time to get into the details of all areas of your operations, it's amazing the improvement opportunities that you can find, and good data analytics is the tool that can help with that.
Which areas of your business are you analysing and what are some of the interesting discoveries that you have made?