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In the world of advanced analytics led digital transformation, many organizations start their journey by optimizing the most tangible and immediate levers; typically price, promotion, or product recommendation. This is often framed as “Next Best Offer” (NBO), and for good reason: it’s measurable, impactful, and relatively easy to isolate. In retail, for instance, price elasticity…

In most large enterprises, advanced analytics is no longer a novelty. In these organizations, large investments have often been made in data infrastructure, data science teams, and machine learning capabilities. Despite these investments, however, most analytics programs remain highly fragmented, tactical, and disconnected from the broader business mission. They lack a North Star; a unifying…

In an era where artificial intelligence (AI) and machine learning (ML) are transforming industries, ensuring robust governance of these models is crucial. Model governance has long been a well-established practice in the financial services industry, where model risk management is guided by three core risk concepts: Exposure, Reliance, and Uncertainty. These principles provide a strong…

Marketing has always relied on data to make informed decisions, but the advent of advanced analytics has redefined how data can be leveraged to drive impactful outcomes. While traditional marketing analytics methods have served their purpose for decades, advanced analytics introduces a new paradigm—offering deeper insights, better personalization, and enhanced efficiency. This article explores the…

Pricing plays a crucial role in the success of any business, whether in retail or wholesale. The strategies behind retail and wholesale pricing vary, as they cater to different segments of the supply chain. Wholesale pricing is focused on selling goods in large quantities to retailers or other businesses, while retail pricing targets end consumers.…

For many businesses that want to move up the Analytics Maturity Curve , there’s a persistent myth that actionable insights can only emerge from pristine data. Business executives in these companies frequently dismiss their organization’s analytics potential, believing their data is too “dirty” or unreliable to power advanced insights. The truth, however, is that no…

Organizations striving for data-driven decision-making often follow a journey along an analytical maturity curve. This maturity curve represents the stages through which businesses progress as they leverage data to generate increasing levels of value. Each stage reflects a greater degree of sophistication, moving from basic descriptive analysis to advanced predictive and prescriptive analytics. Understanding each…

Risk and Reward: Optimizing Cut-off Points in Binary Classification Binary classification is a cornerstone of supervised machine learning. In this domain, models often output a continuous probability score, predicting the likelihood of an outcome being positive or negative. A critical step in turning these probabilities into actionable decisions is selecting a cut-off point, the threshold…

What if the cost of having machines that think, is having people that don’t? – George Dyson from the book Turing’s Cathedral This is a relevant question from George Dyson’s master work: Turing’s Cathedral; which explores the early development of computers, nuclear weapons, AI, and more. While this quote warns against relying too much on AI to…