, Aug 17, 2021
Automation and AI need the right foundation to deliver value
Remember the buzz of the first Tesla sports car? Here was a beautiful thing with neck-snapping acceleration that wouldn’t kill the planet. The waiting list stretched to the moon and back, despite the price-tag.
But when you started thinking about the infrastructure needed to deliver all that glamour, some of the shine wore off – where to charge it, how far it can go before it needs plugging in again, what happens when that expensive battery goes like your old phone and won’t hold its charge?
Cloud’s trajectory has been similar, moving from the exciting prospect of an end to inflexible, complex capital thirsty IT, to the recognition of the number of moving parts around it that still need to be managed for it to fulfil its potential.
Now automation, and beyond that Artificial Intelligence (AI), promises to be the next big thing. How do businesses establish the right foundation to reap maximum benefit and avoid the kind of pitfalls that we’ve seen with some Cloud implementations?
This blog explores the critical role of data management in creating the right foundation for AI enabled business. Other blogs in this series cover the key role of process, IT and data alignment, and freeing IT from the constraints of a capital-led expenditure model. There’s also an eBook covering the critical role of data management and its importance in an AI enabled world.
Start by working out where you want to be
The journey to an effective AI enabled enterprise should start with the business asking at least two key questions; ‘Why are we automating?’ and ‘What are our data management priorities?’.
If it starts with a long IT shopping list for Robotic Process Automation (RPA) and AI tools because you have to get on the AI bandwagon, it might be time to rethink that strategy.
Asking ‘Why are we automating?’ helps identify the business areas where automation can deliver most benefit. This requires business process mapping, another critical foundation for automation and AI which we explore in another blog.
‘What are our data management priorities?’ tells you whether the most pressing need is around data compliance, cost, maximising value from data or a combination of all three.
Automation and AI need to be securely founded on solid data structures. Understanding your data priorities helps you understand how much groundwork is needed to establish that foundation.
Build the symbiotic relationship between data and process, IT and automation
Where an organisation’s immediate data priority is compliance or managing data storage costs, it indicates a need to focus on establishing or strengthening information lifecycle management (ILM). Our ebook on Data Management in the Age of Data goes into detail on how to build strong data management across the business.
For an organisation where data structures already meet compliance and regulatory requirements, and data storage costs are under control, priorities are likely to be around maximising data value.
This is where the value of the symbiotic relationship between data, process, IT and automation starts to show itself.
Consider the process of moving from ad-hoc departmental procedures for staff holiday requests to a common, HR owned, automated process.
Not only does this free up departmental administrative resources for more rewarding work, it removes data duplication and can reduce the organisational data footprint in other ways.
A robust process for managing staff holiday, with the right checks and balances, can remove the need to retain years of staff holiday requests in case the process is challenged. A significant source of data redundancy is data that doesn’t directly feed a process but is retained ‘just in case’.
This cycle of mapping and continually improving processes founded on robust data structures is at the heart of effective automation and AI deployment. In turn, the cycle drives ever more efficient use and management of data.
Data, process, automation and AI is a single business led journey
Following the crowd and bolting automation and AI on to weak business processes and data management invites the same kind of pitfalls as we’ve seen with some organisations’ Cloud adoption. It’s a bit like buying a Tesla without checking where you can plug it in.
Driving automation from business priorities, understanding and strengthening the business process and data management landscape then growing your automation strategy from this, and treating AI as the end stage; all of these elements will help create a strong, data and process-based foundation for the automated, AI led business.
Logicalis UK has helped many clients deliver success in their data management, process, automation and AI journeys.
Download our ebook to find out more about the data management led journey to AI, or email firstname.lastname@example.org to find out more.