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Analytics is currently treated as an emerging profession that comes from a convergence of techniques rooted in the fields of statistics, operations research, industrial engineering, computer science, as well as the fields of psychology and decision analysis. A leading professional body, INFORMS, defines analytics as: “The scientific process of transforming data into insight for making better decisions” (Robinson, 2012). We can treat analytics as an emerging profession because the body of knowledge required for analytics has become extensive, and business people have started to designate teams and departments as being specialists in analytics. An ecosystem of service providers has evolved for this profession, including conferences, degrees, professional consulting services, certifications, etc. Analytics technologies support algorithms for forecasting, optimization, visualization, etc. using techniques such as linear regression, machine learning, design of experiments, simplex, queuing, simulation, etc. We should also include Business Intelligence (BI) and Data Warehousing (DW) under the umbrella of analytics technologies. Analytics is best understood as a business asset that is used to improve decision-making and execution. This chapter outlines the analytics landscape and aims to help organizations gain a shared understanding of issues that must be addressed to plan, build and use the analytics asset.

PurposeThe paper attempts to frame the challenge of managing the transition to a sustainable economy by way of a conceptual model consisting of a zero-footprint regulatory regime and a sustainability fund.Design/methodology/approachA conceptual model of the sustainable industrial revolution has been developed based on the learnings from industries such as originators (mining), farming, pharmaceuticals, pesticides and chemicals and long-lasting artefacts against an overall perspective.FindingsIt is suggested to have an institutional structural mechanism in place to ensure that footprint is minimized through recycling including refurbishing, resale or transformation. This includes management of recycling businesses through execution of a zero-waste regulatory regime that will build and use a sustainability fund.Research limitations/implicationsThe limitations of the paper are arising out of the topic being an issue of gigantic proportions with immense complexity. An attempt has been made to bring out the inescapability and the imperative of a sustainable industrial revolution.Practical implicationsThis paper presents practical aspects such as collusion between trash and recycling businesses, land use and social aspects of criticality of public support. If implemented, the suggested model can make a paradigm shift in the way firms, industry and governments can handle the challenge of sustainability.Originality/valueThe value of this conceptual paper lies in an attempt to extend the learning organization framework to the concept of a regulatory model for sustainability that is not limited to the definition of a firm but stands extended to industries and to the economics, land use and demographics of the planet.