EDITOR ’ S QUESTION
The sheer number of technologies , applications and systems that many enterprises are working with daily means they run the risk of being overwhelmed by the very solutions that are designed to help them . To mitigate against this , there ’ s a lot to be said for getting the base systems well established before the finer tuning takes place . So , for example , get the ERP solution installed and up and running before focusing on the additional value-add stuff , which invariably involves finetuning what ’ s already there to suit the often unique needs of the business .
Choosing a solution with pre-built processes and configurations that are relevant to the industry the enterprise operates in goes a long way to helping with this , not only enabling a more predictable , quicker implementation but delivering a faster time to value too . A time-to-value analysis before any implementation takes place can be a great help , setting out just what are the timescales to be expected , not only in terms of implementation but how long the enterprise can expect to wait before the technology investment delivers real , tangible value .
The key to overcoming the very real threat of drowning in data is to harness the existing data to extract optimum levels of value from the swathes of data available .
– to instead focussing on a single , unified strategy for data management . At the heart of this is the need to not only store all data in a single repository , such as a data lake , but to then restructure this data to become even more powerful and , ultimately , more effective .
Through the application of advanced AI and Machine Learning technologies , it ’ s possible to turn this amalgamated data into meaningful , intelligent insights that inform better , faster and more effective decisions , making optimum use of the huge amount of data that ’ s available to enterprises today . p
Also , an enterprise ’ s core systems should be ready to integrate with a whole host of other solutions that the business might already have or systems that the business is considering implementing . This makes life easier for the in-house IT team , meaning much less work ( not to mention expense ) involved in bringing everything together .
Additionally , the key to overcoming the very real threat of drowning in data is to harness the existing data to extract optimum levels of value from the swathes of data available . This warrants a real shift from talking separately about data sources , data storage , data rationalisation , data enrichment and data visualisation – the list is almost endless
PHIL LEWIS , SENIOR VP OF SOLUTION
CONSULTING , INFOR
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