Why move? Because being a data producer is short-term and expensive
Businesses today have the capacity to produce a lot of data. But how often does this data remain in department silos instead of being joined up cross-departmentally to create a bigger picture?
And when a new research study is immediately commissioned to answer some difficult consumer behaviour or competitor intelligence questions being asked by your board or the new MD, the cost of this new study is outweighed by the hope that this time the additional data will quickly throw up the answers you want to give them.
This is what is meant to be a data producer; it is reactive, short-term and compartmentalised. It is also an expensive way of operating and has the potential to lead you in the wrong direction as the all-important context has not been applied.
An insight generator on the other hand is interested in big picture understanding, which is gathered from different projects and different resources, and presented with context. When a new research study is commissioned, the findings are tangibly linked to the overall business goals rather than to individual projects and therefore can built up into a comprehensive view of your customer, the market you operate in, your brand performance, and much more.
It is a much more sustainable and valuable way of handling data and information
There is more value in accumulated understanding than in a single new investigationThe Insight Management Academy
Making the move from data producer to insight generator is as simple as rebalancing the need for new research with the development of an insight library for your business.
This can be done in five basis steps
Step 1 is to run an insight audit of all the data, research and studies available to you from different departments, categories, internal and external.
Step 2 is to summarise the key findings from all the research/data sets/reports completed or acquired in the past year from all the different departments. We recommend this is done in the form of a one-page summary for each study or piece of research, which is tagged and stored in a database that is easily accessible to your management team
Step 3 is to look back over the past 5 years to see what data can be used as bench-markers to identify trends that have been developing over the longer term. Add these longer term trends to the key findings
Step 4 is to match the key findings with your business goals, for example new product development, marketing communications, acquisitions, target markets, brand future-proofing.
Step 5 is to implement a single analytics application across all departments to eliminate data silos and join the dots between the different data sets.
Moving your business from producing data to generating insight is the key focus of our Insight Management Framework. Find out more here >