In today’s complex and uncertain business world, a manager’s duty involves making informed decisions. From strategic, once-in-a-lifetime choices to high-volume automated responses, decision-making is essential for companies’ competitive advantage. However, our conventional practices, like building linear Excel spreadsheets and expecting them to deliver accurate evaluations, are no longer adequate. Instead, we need to embrace the future of decision-making, underpinned by Decision Intelligence.
Adopting a holistic approach to decision-making, which is data-driven and interconnected across the enterprise ecosystem, is imperative. Each decision influences the organization and can reverberate across all aspects. Decisions need to be connected not only hierarchically (strategic, tactical, operational) but also more broadly in a networked sense. Sharing data and insights across organizational boundaries is integral to this approach, pushing the boundaries of traditional decision-making practices.
In this vein, the enterprise digital twins concept presents a significant opportunity. By mirroring complex, real-world systems within a virtual environment, digital twins can expedite the practical implementation of Decision Intelligence. They offer a sandbox for exploring, testing, and fine-tuning decisions before rolling them out on a larger scale, thus bringing a new level of agility and precision to decision-making.
According to Gartner’s report “Top Strategic Technology Trends for 2022: Decision Intelligence”, organizations should focus on creating capabilities for rapidly composing and recomposing transparent decision flows to cope with business complexity and uncertainty.
This report highlights that by 2023, more than 33% of large organizations will have analysts practicing Decision Intelligence, including decision modeling. The report also emphasizes that decision intelligence bridges the gap between artificial intelligence (AI) and human decision-making, enabling an enhanced and automated/augmented decision-making process. One key component of Decision Intelligence is the ability to quickly adjust decision flows and models, which is essential for disruption-ready and resilient organizations. The ability to create a synergy and mutually complement socio-technical systems where AI tools empower human weaknesses and contemporary challenges of AI are handled by humans will dominate the future of management.
Therefore, the role of a decision engineer will be at the forefront of the next labor revolution we will witness soon. It will be a crucial multidisciplinary collaboration role liaisoning the gap between business domain experts, process experts, and AI specialists.
Given the increasingly competitive labor market, I would lean towards a decentralized Decision Intelligence operating model within the organization, where business leaders will be empowered with platform capabilities that allow them to evaluate options and make better decisions, thus increasing the overall agility and resilience of the organization. This, in turn, might affect the vendor landscape that today is overly focused on engineering capabilities but need to make a tradeoff in favor of people without or with limited coding skills. It is reasonable to expect more no-code or low-code platforms.
Decision Intelligence is heralding a new age in business, transforming decision-making through the synergy of human acumen and artificial intelligence. The novel role of decision engineers is central to this evolution, facilitating collaboration between domain experts and AI specialists. Enhanced by the precision of enterprise digital twins, this shift towards decentralized Decision Intelligence, supported by low-code/no-code platforms, paves the way for increased organizational agility and resilience. In an increasingly competitive business landscape, Decision Intelligence is not a mere trend but a strategic linchpin for navigating the complexities of our new normal environment.
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