One of the problems with traditional supply and demand economics is trying to predict what consumers are going to want when and where they will want it. Produce too much, and you’ll end up having to sell it at a discount. Produce too little, and your competitors will take your market share.
The digital age has produced a galaxy of data that can be used to improve tracking and predicting consumer behaviour, and more businesses and organizations like the BC Egg Marketing Board are using business analytics tools to improve operation efficiencies.
Since it started using IBM [NYSE:IBM] Cognos business analytics software two years ago, the board has saved about $67,000 a year and has better information on the production cycles of its 130 egg producers and the 816 million eggs they produce each year. It has also reduced the workload of its inspectors by about 66%.
“As a province, we can look at [if] we have the right supply of eggs at the right time,” said Anne-Marie Butler, the board’s director of finance and administration.
Since adopting IBM business analytics and arming its inspectors with tablets – digitizing what used to be a paper process – the board and its 11 staff have improved their efficiency and that of its producers by giving them access to information they’ve never had before. Using a new web-based database, B.C. egg producers can now access information on their production cycles and those of other producers.
“They’re going to be able to determine when they need to add to their flocks, when they need to replace their flocks, when they need to scale their production,” said Mychelle Mollott, IBM’s vice-president of worldwide marketing.
Business analytics is not new, but the sheer volume of data that’s now out there requires new analytics tools.
“Analytics helps people make sense of the big data,” Mollott said. “It helps them drive business decisions that can fundamentally change how they’re performing.”
Duncan Stewart, author of Deloitte’s annual Technology, Media and Telecommunications predictions, said it’s not just the volume of data that’s a challenge for modern business analytics, it’s also speed.
New big data tools allow massive amounts of information, including unstructured data (emails, phone calls, video), to be analyzed as soon as it’s released. For example, financial institutions use big data tools to analyze banking transactions to detect credit card fraud.
One of Vancouver’s most successful e-commerce companies – BuildDirect – has developed its own set of analytics tools to more precisely predict what kinds of building materials consumers will want in a given region at a given time.
The company has spent considerable effort developing its own algorithms to analyze customer behaviour via the company’s website.
BuildDirect executive officer Robert Banks said the guesswork in traditional analytics is expensive because manufacturers often over-produce products they can’t sell because they can’t accurately predict what consumers will want.
“The risk is millions of dollars, and they’re always wrong,” Banks said. “If they launch 200 new colours, they might have 50 that are correct. The other 150 colours, they had to produce them and now they have to sell them at discount.If we can help them with predictive data to avoid all of those losses, now they can be that much more efficient, and we can go to market with a better priced product.” •
