Speak the same language

The silent killer of so many Analytics programmes is people’s inability to have, keep and retain standard terms. A term that may be well understood when the content is created does not necessarily continue to mean the same to the whole audience of the content for the whole life of the content.

In this video, we look at the well-used metric of COGS or Cost of Goods Sold (COGS = [Cost of Materials] + [cost of labour]), this is simple to understand and utilise, with a manufacturing centred audience, however as your journey to a data culture continue and you start to use data in a broader sense to establish your business goals and objectives it becomes important to make sure that you understand when you need to make changes to lowers COGS vs similar metrics like COS(Cost of a Sale). The COS relates to the activities made to achieve a sale, were adverts used, did you have to send sales teams to meet the client, was a demo needed, loan equipment provided etc… COGS and COS affect the profitability of a product but in very different ways. ISo you have to make sure that your audience understands both terms, the way they are calculated and the impact that would be made of a change. For example, if you commit to advertising @£1,000 per month, feedback has shown that your product would be better received if it were a different colour, but that adds £1 to the per-unit cost, how should we make the product more profitable, should be reduce advertising or should we make the changes suggested by feedback? You can see how a simple lack of understanding of the difference between COGS and COS can lead to different answers.

The risk posed by this is only exacerbated by the often culture present in many businesses, where it is often seen as a weakness to ask, “What does that mean?” really, the opposite is true. This is such a common aspect of Corporate Culture that Simon Sinek even calls it out. There is nothing wrong with being the “Dumbest” in the room: using it to pull together a clear understanding of what is being presented and what is being suggested is a must if a business moves towards the more advantageous Data Culture that supports Information based Decision making.

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