With all the hype now focused on Omni-Channel what’s happened to the last key development in Retail Systems? Real Time Data!
It wasn’t and still isn’t unheard of for systems to batch data updates both to and from central and other key systems , Price Changes, Promotions, Inventory Levels, Sales Activity.
But then the holy grail of Real Time Data came along, know what’s going on in your stores, spot slow selling lines early and have impromptu sales / price reductions, see spikes in consumer demands as the rain or sun strikes in certain areas BUT wait this is all great in theory, practice however is a very different thing.
How many retailers actually sit there and monitor sales of umbrellas to know its raining in that area? one of many weather forecasting apps could have told you that 3 days earlier and you could have actually shipped the stock to the store and advised the staff to put them at the front of the store that very morning instead of waiting for it to start raining.
So much goes in behind the scenes to create a promotion, labels, signs, moving stock so its logically close to the other items in the promotion. Why would you reduce a range by 10% at 3 o’clock on a Friday after coming back from lunch to see that your behind in your targets, without designing someway to actually tell the customer be that by email and or in store advertising, likely you are then including at least 2 or 3 other departments, don’t forget this is 3 o’clock on Friday, they want to go home and not get stuck pulling together your latest promotion.
So Real Time Data… Do we need it? Do we use it?
The intention was to provide immediate access to data to allow decisions to be made using the latest data but is this too much, do we really need this level of data or do we really just need data up to the end of the previous day but actually pre-processed into useful formats, guaranteed to be available a when you need it and tied in with external data sources to provide the complete picture.
Useful external data could include Weather, local events, national events (World Cup football for example), school holidays, sales / promotions from other Retailers. This kind of data enables us to use what’s available to interpret what we see in spikes / dips and understand the impact of the wider environment on all touch points. Maybe during the World Cup you need to drive people to your website because they aren’t going into stores, or during the extreme summer weather people like spending time in your nice air conditioned store dwell times might increase as people cool off but what would entice them in or to make that purchase while they are there?