Today's business landscape is arguably more competitive and intricate than ever before: Customer expectations are at an all-time high, and businesses are tasked with meeting (or surpassing) those needs while simultaneously creating new products and experiences that will provide consumers with even greater value. At the same time, many organizations are constrained by limited resources, grappling with budgetary constraints, and dealing with persistent business challenges like supply chain delays.
Businesses and their success are defined by the sum of the choices they make every day. These choices (good or bad) have a cumulative effect and are often more interconnected than they seem to be or are treated. To keep up in this demanding and constantly evolving environment, businesses need the ability to make decisions rapidly, and many have turned to AI-powered solutions. This agility is crucial for maintaining operational effectiveness, allocating resources, managing risk, and supporting ongoing innovation. Simultaneously, the increased adoption of AI has exacerbated the challenges of human decision-making.
Problems arise when organizations make decisions (leveraging AI or otherwise) without a solid understanding of the context and how they will impact other aspects of the business. While speed is an important factor in decision-making, having context is paramount, albeit easier said than done. This begs the question: How can businesses make swift and informed decisions?
It all starts with information. Businesses are acutely aware of data's key role in their success, yet many still struggle to translate it into business value through effective decision-making. This is mainly because good decision-making requires context; unfortunately, data does not carry with it understanding and full context. Therefore, making decisions based purely on shared data (sans context) is imprecise and inaccurate.
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