FEATURE
Management ( APIM ) and Service Buses to speed integration and prevent data silos .
Get your data strategy sorted
Once the business applications have been selected and the integration work is done , it ’ s important to focus resources on data strategy . This will help ensure that all data is of the highest quality , and will help drive gains in profit , efficiency , innovation and customer experience . Steps that businesses might take to achieve this could include :
• Optimising performance and availability of an existing data environment
• Prioritising data systems migration
• Building or expanding data warehouse or data lake environments to cope with current and future data volumes
• Modernising data systems where necessary
• Building or expanding data analysis capabilities for improved business intelligence
According to findings in our latest Mid-Market IT Priorities Report , many companies are already taking this approach . Indeed , addressing the performance of existing data environments and migrating data systems are joint top data strategy priorities for mid-market IT decision-makers .
The findings also showed that over a third of mid-market companies plan to build or expand
data warehouse or data lake environments in the next 12 months . This indicates a wish to centralise data and improve analytic and insight capabilities . It also reaffirms the importance of establishing solid foundations to ensure data is accessible and performant .
Looking to the future
As AI evolves , prioritising data availability for integrated applications and wider business intelligence initiatives will become even more important . AI ’ s ability to pull data from across an organisation is already a game-changer . However , further down the line , AI is likely to revolutionise ERP strategies and become embedded in even more ERP software and business applications . As such , AI may also be a key piece in the puzzle in terms of delivering fully integrated business software solutions and removing siloed data .
It ’ s important , however , to stress that despite the incredible speed at which AI is evolving , these kinds of advances will take another three to five years . That said , companies do need to start laying the foundations now . First , they should ensure much closer application integration . They should also reevaluate their data strategy in readiness for the greater role that AI will play in business application advances and ERP implementations . x
32 www . intelligentcxo . com