CASE STUDY
Over the last decade or so , the trend towards Digital Transformation has rapidly gained pace , riding the accelerating wave of technological development and driven by increasing competitive pressures , emerging growth opportunities and the need to increase efficiency and productivity . Then the pandemic hit , adding to existing volatility and vulnerability , with disruption in global supply chains .
In this environment , it has never been harder for the CIO to be the informed voice of reason and competitiveness when it comes to enterprise technology .
Increasingly , every new effort , whether it is Digital Transformation , environmental , social and governance ( ESG ), sustainability , or a new enterprise strategy , it falls to the CIO , in one form or another , to implement with digital tools and services , making it even more important for the CIO to be informed , effective and decisive .
What if there was a way to make those decisions in a better-informed , more structured way , and faster ? And could such an approach be developed for the whole enterprise ?
Technical and organisational challenges
As the pace of technological change becomes more rapid , complexity too , has crept further into enterprise data architectures .
A 2023 industry survey found that 98 % of senior IT leaders have been impacted by increasing cloud complexity in some capacity , potentially leading to poor IT performance , loss in revenue and barriers to business growth .
Added to this , data complexity has grown as a major pain point for companies globally , with tech executives feeling the pressure to contain its impact on the business . Technical and organisational challenges may further stunt their enterprise strategies , with 88 % citing working across current cloud environments as a barrier , while 32 % struggle to align on a clear vision at the leadership level .
Complex decisions
This complexity is impacting the business too , as diversification , changing consumer demand , multiple product , brand and service lines all must be managed and analysed . While this has always been a challenge , omnichannel engagement and the emergence of new consumption trends , has accelerated the situation , further burdening the business .
Research has found that nearly two thirds ( 65 %) of business leaders report that decisions they make are more complex now than just two years ago , with more than half ( 53 %) admitting to facing more pressure to explain or justify their decisions .
Technology and consumer brands can find themselves managing multiple products , distribution channels , promotion campaigns and marketing channels at any one time , each more data rich and diverse than ever before .
AI can deal with large amounts of data and reduce complex patterns into manageable loads . This strength of AI means infrastructure and data complexity can be reduced and minimised through optimised design and AI-monitored operation .
When decision-makers have trustworthy AI to cut through this complexity and the deluge of data , they
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