Project

big data monetization

Goal: business planning with big data - value chain

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Project log

Roberto Moro-Visconti
added a research item
Traditional business planning follows a managerial top-down approach where forecasts are conceived within the firm and occasionally compared with market returns. The increasing availability of timely big data, sometimes fueled by the Internet of Things (IoT), allows receiving continuous feedbacks that can be conveniently used to refresh assumptions and forecasts, using a complementary bottom-up approach. Forecasting accuracy can be substantially improved by incorporating timely empirical evidence, with consequent mitigation of both information asymmetries and the risk of facing unexpected events. Network theory may constitute a further interpretation tool, considering the interaction of nodes represented by IoT and big data, mastering digital platforms, and physical stakeholders. Artificial intelligence, database interoperability, and data-validating blockchains are consistent with the networking interpretation of the interaction of physical and virtual nodes. Flexible real options represent a natural by-product of big data consideration in forecasting, with an added value that improves Discounted Cash Flow metrics. The comprehensive interaction of big data within networked ecosystems eventually brings to Augmented Business Planning.
Roberto Moro-Visconti
added a research item
Traditional business planning follows a managerial top-down approach where forecasts are conceived within the firm and occasionally compared with market returns. The increasing availability of timely big data, sometimes fueled by the Internet of Things (IoT), allows receiving continuous feedbacks that can be conveniently used to refresh assumptions and forecasts, using a complementary bottom-up approach. Forecasting accuracy can be substantially improved by incorporating timely empirical evidence, with consequent mitigation of both information asymmetries and the risk of facing unexpected events. Network theory may constitute a further interpretation tool, considering the interaction of nodes represented by IoT and big data, mastering digital platforms, and physical stakeholders. Artificial intelligence, database interoperability, and data-validating blockchains are consistent with the networking interpretation of the interaction of physical and virtual nodes. Flexible real options represent a natural by-product of big data consideration in forecasting, representing an added value that improves Discounted Cash Flow metrics. The comprehensive interaction of big data within networked ecosystems eventually brings to Augmented Business Planning.
Roberto Moro-Visconti
added a research item
The research question of this paper is concerned with the investigation of the links between Internet of Things and related big data as input parameters for stochastic estimates in business planning and corporate evaluation analytics. Financial forecasts and company appraisals represent a core corporate ownership and control issue, impacting on stakeholder remuneration, information asymmetries, and other aspects. Optimal business planning and related corporate evaluations derive from an equilibrated mix of top-down and bottom-up approaches. While the former follows a traditional dirigistic methodology where companies set up their strategic goals, the latter are grass-rooted with big data-driven timely evidence. Real options can be embedded in big data-driven forecasting to make expected cash flows more flexible and resilient, improving Value for Money of the investment and reducing its risk profile. More accurate and timely big data-driven predictions reduce uncertainties and information asymmetries, making risk management easier and decreasing the cost of capital. Whereas stochastic modeling is traditionally used for budgeting and business planning, this probabilistic process is seldom nurtured by big data that can refresh forecasts in real time, improving their predictive ability. Combination of big data and stochastic estimates for corporate appraisal and governance issues represents a methodological innovation that goes beyond the traditional literature and practice. Keywords: Revenue Model, Forecasting, Free Cash Flow, Real Options, Valuation Metrics, Stochastic Simulation, Sales. Acknowledgement: This publication has been financed with research funds from the Università Cattolica del Sacro Cuore of Milan, Italy (Line D.3.1. /2018).
Roberto Moro-Visconti
added a research item
Public Private Partnerships (PPP) represent an increasingly frequent investment pattern where composite stakeholders interact in joint initiatives. Alignment of interests and consequent composition of conflicts is driven by the business purpose of the shared corporation, represented by a private Special Purpose Vehicle (SPV) within a Project Financing (PF) investment package. Corporate governance implications go beyond the traditional contraposition between ownership and control, showing cooperative patterns where the value is co-created and distributed. Big data-driven networks represent a trendy issue that connects public and private stakeholders through digital platforms where data are shared in real time. Information asymmetries and governance concerns are consequently softened.
Roberto Moro-Visconti
added a research item
Healthcare investments are faced by the need to match growing expenses, due to ageing population trends, with public budget constraints. Infrastructural PF packages are by now popular and effective, although they are rigid and long-termed. Big data-driven value chains add unprecedented information to project financing (PF) and public private partnerships (PPPs), especially in healthcare investments. Big data and Internet of Health sensors, currently adopted in telemedicine, can be applied even to PF strategies, providing useful information to data-driven business plans. Public and Private Partners interact through networking big data and interoperable databases, boosting value co-creation, improving Value for Money, and reducing risk. Policy makers can conveniently use networked big data to enrich their feasibility plans, whereas private managers may extract precious information from public healthcare databases. Big data can also help shortening supply chain passages, boosting economic marginality and easing the sustainable planning of smart healthcare investments.
Michele Marconi
added a research item
The flow of big data-driven information across the web, known as Internet traffic, is growing in volume, velocity, variety, veracity and value. Scalable data systems connected through the web or other IT platforms as mobile-friendly apps produce a network where information and experiences are shared in real time as never before. Digital value chains are based on sequential steps where big data are captured, stored, processed, and shared. Monetization is the last step, which transforms added value into cash. Big data are present at any stage of the value chain, so network theory is relevant for all steps of its upgrading. Value co-creation is an under-investigated topic, especially considering the hidden potentials of big data, such as networking attitudes of the users that generate data itself, and thus useful for predictive analytics within collaborative communities. Big data-driven business models revolutionize planning with hidden information and extract value from data that are considered a worthy asset. The value of data grows exponentially when it is connected and combined with other heterogeneous sources. This shows the importance of data fusion and big data integration (interoperability). This study proposes a new research avenue with an interdisciplinary approach to big data monetization, generating a shared added value that can boost their exploitation.
Roberto Moro-Visconti
added an update
I am preparing an interdisciplinary research about big data monetization with value co-creating digital platforms
Big data vale chain starts with capture, followed by storage, processing (data mining ) and consumption (sharing )
Monetization is the last fundamental step.
 
Roberto Moro-Visconti
added a project goal
business planning with big data - value chain