In a world where uncertainty is the new norm, where technology is getting smarter, where robots are automating and simulating human activity, and where big data is getting bigger, the pace of winning and losing is getting even faster. The margin for error for organizations is now even smaller, meaning high-quality decisions grounded in insight have never been more important.
It's true: Technology is capable of automating a lot of what we used to do when it comes to analyzing data. It can even take this a step further and simulate some of our thought processes. That said, technology has one shortfall: It is not human, and generating insights is an inherently human process that needs human traits to interpret what is happening.
The beginning of the insight process involves being clear about what you are being asked to analyze. I quickly came to appreciate that the significant first question was not "what?", but "so what?"
Faced with a deluge of data, finding a way to combine these human qualities with the tools on offer will provide organizations with more opportunities to make high-quality decisions grounded in great insights.
Define, Determine, Deliver
I propose a ten-step approach to accelerate the process of generating and delivering insights, which forms the basis of the Define-Determine-Deliver model.
The model draws on a number of sources. First and foremost, it is based on my experiences of working with some of the largest insight-driven companies in the UK and US. (Deloitte defines an insight-driven organization as "one which has succeeded in embedding analysis, data, and reasoning into its decision-making processes".)
I was able to observe best practice in the way these companies collected and organized huge amounts of diverse data, and I gained a profound understanding of performance and how they were able to engage their people to take the right next steps, which led to stronger performance.
Second, the model takes up the themes being debated by practitioners, experts, and authors, in terms of how to organize and interpret the huge, diverse data sets organizations are now collecting. And the more diverse and complex the data, the greater the challenge of communicating insights.
The model consists of three stages:
- The define stage will help you clarify what you need to do and why
- The determine stage offers a set of principles to help you generate insights
- The final stage looks at how to deliver your message to achieve the level of impact and influence your insights deserve
Define: Planning Your Analysis
1. Be clear on the value of your insights. The beginning of the insight process involves being clear about what you are being asked to analyze. Over the years of working for a number of insight-led companies, I quickly came to appreciate that the significant first question was not "what?", but "so what?"
Understanding the value (the "so what") that your insights will add helps you engage with what the person requesting the information is trying to do. When you are informed and engaged, you build a more relevant and more focused analysis plan.
Tip: If the person making the request hasn't already outlined the "so what", asking them "How will the analysis help?" is a good way to understand what they are hoping to gain from the insight.
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