Strengthen Your DC Operations with Time Series Analysis.
It’s a gray and cloudy day outside as I’m writing this and according to the weather report, rain is on the way. Too bad. I had hoped to squeeze in a run over lunch. Luckily, I have about an hour before the rain starts, so if I go a bit earlier than usual, I should be able to make it.
But imagine if the only information I could get about the weather was what I could see outside right at the moment and monthly average temperatures. If the weatherman tells me that it’s typically warm and sunny in April, well, that doesn’t tell me anything at all about what to expect tomorrow, or this afternoon. And it certainly doesn’t help me to know that right now is my window of opportunity.
This kind of stale data is unfortunately all too common for warehouse analytics.
At CognitOps, we made a decision early on to go beyond daily averages and static analysis. Tracking individual changes over time for every dimension of a warehouse enables us to help operators make better, faster decisions.
So rather than keep track of the total number of orders shipped, or the average daily pick rate we have decided to store individual events as they happen in real-time. We store the time when any particular order was packed, when a warehouse employee moved from one station to another, when a particular batch was released. And we never delete any of it.
Because we have all of that information — and because we collect it live — we don’t only know your operation’s typical performance, but we can tell you how your building is performing right now. Even better, we recommend actions that increase throughput and reduce costs.
Managing a time series data set is substantially more complicated than analytics data that might, say, power a reporting dashboard or inform a res-slotting exercise. Until recently, the technology to store and process such huge quantities of data simply didn’t exist. At CognitOps we’re bringing the big data capabilities available to financial services and social media marketing to the warehouse.
If you’d like to see a demo of how our time series approach enables operators to make game-changing real-time decisions with the best possible data, contact us at email@example.com.