Did you measure that right?
Here at Amack, our new Decision Science colleagues and platforms are our secret weapon. Sounds pretty fancy, doesn’t it? It’s just common sense really. CEO Andrea McGeachin explains…
To be honest, in its early days, I found decision science to be pretty confusing, before it started to become interesting to me. Initially, I was simply excited by the thought that all the data could be thrown into a pot and an answer would pop out like magic! I’m a born optimist but often disappointed, and of course it was not that simple. To an extent, you can simply shove all your data into the Decision Science Pot and you will get answers. But you need to be prepared to have what you thought would be the outcome destroyed and have alternatives you’d never considered thrown your way at the same time.
Of course, it’s all about asking the right questions and knowing what you are measuring. Get on top of that and the use of multiple data inputs can give really useful insight into your business, offering information that can transform decisions and let you know that your idea was fantastically right or quite a way off.
So let’s think about what you want to measure and how working with our Decision Science platforms and data experts might help.
Measuring sales progress is completely different with a data scientist by your side. I’ll give you an example. We visited an expo with a client recently. We’d planned the show timings, messages and presentations and delivered a booth for them. We really thought through who we wanted to attempt to meet and who would do what.
It was a great show; we made 26 meaningful engagements, we helped the client with eight new “deals” and got stuck into the celebrations afterwards. Then the Decision Scientist got started and measured the CRM activity on our content responses and actions and analysed the read receipts in LinkedIn, as well as looking at support tickets from some of the business’s existing customers.
As well as the three straight conversions to business, the other five of the original eight deals, along with six more new engagements from the expo, created a brand new path for the client. All of those companies had a particular experience issue, which the decision scientist spotted via common words in notes from CRM system and LinkedIn. That information helped our clients’ sales people ask the next question correctly and give quality insights.
Measuring things that aren’t ‘just numbers’ is enormously beneficial, but you do need to have the tools and people to convert the many items, words, actions and topics into directional support. I like to view it as a jigsaw; the quicker the picture starts to build, the faster and easier it becomes to complete. It’s not simply about the shape of the puzzle; it’s the colour, the shades, the holes to fill and what’s already there waiting for it.
Speed is vital to success but it must go hand in hand with knowledge. Automated analytics will get you so far, but so often, the human brain has the edge when it comes to measuring those analytics in a smart way. We were eventually able to guide the client we took to the expo to close four deals in less than half the normal time as well as put six other deals in the pipeline.
Decision science used well can deliver smart choices to act on with confidence and deliver information on where not to waste your time, too. But perhaps the most valuable thing about it is that it so often delivers the unexpected. When you open yourself to measuring as much information as you can, and in various ways, you might find the thing that you didn’t even know you were looking for was the answer after all.