Forward-thinking companies aspire to comprehend historical patterns to anticipate current and future trajectories. The unprecedented global crisis triggered by the COVID-19 pandemic has shattered our assumptions about the future, rendering obsolete the trends previously informed by historical data. In this tumultuous landscape, strategic foresight emerges as a beacon of hope, guiding businesses through unforeseen challenges and illuminating their profound implications for organizational resilience.
Amidst the dynamic landscape of contemporary business, data assumes paramount significance across diverse industries. Professionals, spanning from medical practitioners to educators and entrepreneurs, rely on data to shape informed choices. However, a critical issue persists: many data-centric organizations fixate on superficial metrics, which fail to reflect actual market impact. These companies, despite their excessive allocation of resources, unwittingly jeopardize their reputation and strategic direction. When business leaders remain entrenched in historical data, they inadvertently look backward, missing crucial forward-looking insights. Even real-time data, once it reaches their screens, is already dated. Consequently, when unforeseen disruptions emerge, unprepared leaders collide with them head-on, often by mere seconds, yet still within the realm of history. In times of turmoil, these leaders yearn for the steering wheel, eschewing the rear-view mirror’s retrospective gaze.
Despite being known for consistently improving service reliability, a mid-sized Mid-Atlantic utility faced an all-too-common problem with aging infrastructure. Water main breaks were happening at an increasingly rapid rate throughout the utility's 1,000+ mile system with pipes that averaged about 50 years old. There was an increase in water main breaks, resulting in unpredictable outages, expensive repairs, and heavily disruptive road closures for customers. Water infrastructure management is a key component of one of the utility's efforts to improve customer service and reputation. Piloting Xylem's new decision intelligence technology on a hotspot, or area with a high number of breaks they were able to validate this novel risk-based approach. A cost-effective pipeline renewal strategy was developed with the help of an AI-based risk model based on the results of the pilot program. The utility was able to achieve a dramatic four-fold reduction in pipeline failures once this model was implemented across the entire distribution system, reducing their annual pipeline replacement costs from US$90 million to US$20 million. [1]
For your business to be successful in the market on the next patch of dry land, it must respond to disruptions continually. We are living in an age of continuous disruption, where we constantly evaluate and change the way we do business. The data that businesses have relied on for years is now almost worthless in terms of forecasting. Now is the time to rebuild rather than simply re-create or reuse our previous data mining practices. Only 57% of companies rely on data-driven decision-making for business growth, despite 91% believing that it can boost growth.[2]
The actions you take and the results you achieve depend on each decision your business makes from the start. The objective of decision intelligence is to generate a valuable impact for the business. An organization's ability to stay ahead of disruptive technologies and maintain its competitive edge relies on forward-looking thinking and not yesterday’s data. Decision intelligence is the transformation of your business from a data-driven one to a decision-informed one. Data should support our decisions rather than make them for us; otherwise, we're just fishing for insights. A business leader can regain control by switching from a data-driven to a decision-driven approach. Data and analytics can be useful, but they shouldn't be the driving force behind a business's decisions.
No comments:
Post a Comment