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// EDITOR ’ S QUESTION ?
KARL CROWTHER , VP , MEA , ALTERYX
I n today ’ s rapidly evolving business environment , agility is not just an advantage ; it ’ s a necessity . Smalland medium-sized enterprises ( SMEs ), with their ability to pivot quickly , are uniquely positioned to leverage this trait . However , the most successful companies , regardless of size or their sector , share one common strategy : they harness data at scale and speed , transforming it into actionable intelligence . For SMEs , adopting similar data-driven practices can significantly boost their agility and competitive edge .
For SME leaders , fostering an analytics-driven culture starts with a top-down approach that champions the use of accessible and democratised data analytics . Platforms like Alteryx have democratised data analytics , making powerful AI tools accessible to individuals at all skill levels and significantly lowering the barrier to entry . By embedding analytics into their operations from the ground up , SMEs can make informed decisions that enhance efficiency and innovation .
Initiating small-scale AI projects , such as automating the generation of weekly reports , can save significant time and resources . These projects , though modest , are crucial for building confidence in AI capabilities within your team . They act as stepping stones towards more complex automation and analytics initiatives , enabling your business to gradually scale its data capabilities without overwhelming your operational bandwidth .
Enhancing the accessibility of data and automating data processes are essential steps for SMEs . With options ranging from cloud storage solutions , ideal for scalable , computeheavy analytics , to on-premises solutions suited for smaller datasets , businesses can choose the most effective technology to centralise and harness their data . This step is critical in the Digital Transformation journey , particularly in regions like the Middle East where digital innovation is rapidly advancing .
Automating analytics to adapt in real-time to market changes can significantly differentiate digital-native businesses from those burdened by legacy systems . Real-time analytics integrate new data points swiftly , offering immediate insights and enabling businesses to respond quickly to changing market conditions . For example , a retail SME could use real-time sales data to adjust inventory levels dynamically , preventing stock-outs during peak demand periods .
Building AI-led decision systems involves more than automating processes ; it requires mimicking human decision-making to proactively forecast and react to future conditions . This approach is akin to the ‘ recommended for you ’ features on streaming platforms , which utilise historical data to predict viewer preferences . SMEs can use similar dragand-drop technology to transform historical data into predictive insights for strategic planning .
For smaller , digital-native businesses , the shift towards decision intelligence presents a monumental opportunity . By transforming new data into actionable insights , SMEs can react effectively to competitors and market trends . Without the burdens of legacy systems , SMEs are well-placed to turbocharge their operations , enhance decision-making and boost productivity through AI analytics . Now is the time for SMEs to embrace these technologies and secure their place in the future of business .
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SMALL- AND MEDIUM-SIZED ENTERPRISES ( SMES ), WITH THEIR ABILITY TO PIVOT QUICKLY , ARE UNIQUELY POSITIONED TO LEVERAGE THIS TRAIT .
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