Capturing Data And Creating Business Intelligence
I have been writing recently about the requirement for data to be more strategically linked to value creation and how the customer experience (CX) is designed. My most recent articles have focused on a McKinsey research paper that highlights three key areas that executives need to understand:
- Internet of Things; what data is being captured? What is possible to capture? Are you capturing information that can be used to shape insight?
- Capturing value; how does your business define value? What insights do you want to find from the data you have? Can you see, or define, a path from the raw data to business intelligence?
- Insights Value Chain; defining the complete set of requirements that lead from the capture of the data to the creation of intelligence. What physical attributes, properties, systems, or skills are needed for you to make this work in your business?
In this article I want to focus on the insights value chain. This is where we actually capture and use the data and it is critically important to the entire process because even the best analytics are worth nothing with bad data.
What is critical to understand about the insights value chain is that it crosses many different areas of your business – both the business processes and supporting technology. In addition, within these foundations there are many new individual sources of data that need to be controlled for. This image illustrates the idea:
This type of operating model is required because it allows the executive team to plan exactly where data can be captured and turned from raw data into value for the organization. By systematically mapping the insights value chain and then creating actions from each section you can effectively create a list of all the steps required to capture all useful data.
Data collection and data refinement are technology-intensive processes, but many of the activities you need to change will be focus on people or processes and may require the creation or purchase of new tools and governance.
The McKinsey analysis warns explicitly that all areas of the insights value chain are connected. This means that your data capture and ability to turn it into meaningful insights is only as strong as the weakest link across all these areas of the business. I believe that this is a more important factor in some areas compared to others, but the point is valid. Even if you consider data security to be more immediately important than cultural change, you will fail to reach the potential of what is possible with your data without this cultural change.
What this chart really demonstrates is that the creation of value is about far more than just capturing the data. You can capture an enormous amount of data, but with no measurable value for the business if you cannot demonstrate a path from the data capture, refinement, analysis, and then the creation of genuine business insights and value. This process of mapping the value chain creates a clear visual path from data capture right through to business value.
Let me know what you think about this insights value chain idea by leaving a comment here or get in touch via my LinkedIn.
Photo by Ralf Steinberger licensed under Creative Commons