Observe, mechanize, picture
Data has sometimes been referred to as the new oil. The challenge, of course, is to extract that goodness from the depths of the applications and infrastructure in which it rests. This is where data analysis comes in handy, where the information gleaned from the data can paint a picture that can be used to communicate the objectives, the expected outcomes, and the potential risks with the executive leadership team, business unit leaders, and the operational and technical teams that will see their Data-to-Value program through.
With the data picture in hand and a big data plan in place, organizations can begin to identify the best path forward to extract the most value from their data with the best return possible and least risk involved. The story will likely present some top-level opportunities to explore:
- Replicate the story at scale, bringing it to more situations in more locations
- Configure and tune it to make it an even better story
- Apply the story to different parts of the business
- Discard the story as it does not provide a good return, and the investment would be better suited elsewhere
Once the program has a goal, a plan, and is appropriately staffed, you’re close to extracting the value of your data, but there’s one more critical step to take before moving on to something else.
- What business objectives need to be modified?
- What operational workflows need to be adjusted or re-configured?
- What infrastructure and application implementations need to change to support the workflows?
- What changes are required in team skills and make-up to handle the new business processes?
Finally, the inputs and outputs of the new business workflows that are driven by data must maintain confidentiality, integrity, and availability. If the systems or data are compromised, the risks could far outweigh the expected return. It’s imperative to define acceptable use policies, not just for humans but also the machines. The procedures must also be monitored and policies enforced. And a clear path for escalation must be defined for the cases where something goes off the rails.
Don’t forget that extracting value from data is a living process and that the business is only as good as its latest accomplishment. Success will be determined based on an ongoing assessment of what information you have when using it and how well you safely turned the story into reality.