I heard an interesting story recently. A friend works for an organisation that develops and implements digital strategies for businesses in various industries from ecommerce, fashion to NGOs.
We were talking about the importance of data and how it is communicated. (What a surprise that a Tableau person would be talking about that, right?)
My friend described a recent data communication failure that really drove home the importance of clear data communication.
Her agency – let’s call it Agency X – collects, processes and analyses data every day. They use their data to support decisions and to build consensus with colleagues and with customers.
Agency X had been wooing a potential customer – a global operation looking for a complete digital makeover.
This prospect was ready to change everything, from the website’s look and back-end technology to the entire digital brand and how it connects with its brick-and-mortar division. This would be a really exiting win for the agency.
Agency X proposed that it could identify the market, opportunities, and risk by analyzing the prospect’s existing company data as well as information collected from third-party providers and social media platforms. This sort of analysis would be a competitive differentiator for Agency X and would help them land the project they hoped.
Like many organisations, Agency X divides work among many employees, letting specialists take on certain tasks. At Agency X data analysis is completed by analysts. (I know, I was surprised too).
Unfortunately, nobody had reviewed what the analyst would say before the actual presentation. Now that’s not as surprising as it may sound – They were working under a deadline and the analyst was a trusted resource who had proven his ability to extract value from data.
What the team had not expected was that the analysis was so complex that no one in the room had any idea what the analyst was trying to share! He not only failed to convince this important account of the value of his findings, but even the Agency X team was unsure that the analysis was accurate and useful.
They couldn't understand the findings, so they couldn't use them to win the business.
This real example shows how important it is in a business environment to clearly communicate your data findings. As the variety and complexity of data increases, the importance and benefit of engaging everyone within the organisations becomes key efficiency.
And Agency X? They understood their mistakes and are aware that data must be shared across the organisation. That’s how they will make a difference in the market and Agency X now acknowledges it.
Why? The data told them.