"Data" Fuels Automation Capabilities (and Results)!
Shared services executives that recognise the importance of data are quickly putting the right data strategies in place to feed the evolving automation.
Here are 10 steps to implement in order to optimise your data strategy.
- Communicate data management as a core skill and prioritise these roles – With much of the actual work being automated in future, the value-add of the human workforce will be its ability to drive, manage, and work with data.
- Reassess the role of humans – Instead of processing transactions, in future the human workforce needs to re-focus on creating the data sets that feed automation.
- Find, sort, and structure your data – Whether via mapping, identifying the source, structured or unstructured, real or virtual, your team's ability to identify relevant data, and sure it is accessible and workable, and feed it into the appropriate channels will be key.
- Identify the black holes in your data – With the vast majority of valuable data still unstructured, one of your key challenges will be to identify your gaps and fill them.
- Reconsider data flows – Traditional data flows are sequential, but in robotic or intelligent automation, systems can tap into multiple data sources at the same time. This means rethinking data flows from the beginning.
- Data-oriented processing creates an ever-wider circle of influence – More and more activities will be pulled into scope once you open the doors. Plan for this.
- Shifting into more sophisticated tool sets changes requirements – Do you have the data necessary for those new systems? If not, how quickly can you access it? Or does it make sense to reassess your tool implementation strategy?
- Plan for the future – once you understand what data is available, design a plan for the data that isn’t available.
- New tool sets treat data as a virtual lake – Rethink "storage", access, and time.
- It’s not what you do, but how you do it that defines the future.