Strategy Analytics
Agents: System analysts, business analysts, scientist, engineers, technology management consultants;
Strategic moves
Call deep analytics ‘7-S’ model; explore how to ensure a perfect fit among 7- S elements (scope, system, structure, security, strategy, staff-resources, skill- style-support);
Define a set of security goals and emerging technologies accordingly.
Do technology life-cycle analysis on ‘S’ curve : presently at emergence phase of ‘S’ curve.
Explore technology innovation-adoption-diffusion strategy.
Explore innovation model and knowledge management system for creation, storage, sharing and application of knowledge.
Adopt ‘4E’ approach: envision, explore, exercise and extend.
Prof. Gramy Woods and Prof. Helen Fisher are presenting on strategy of technology innovation, adoption and diffusion of emerging technologies against natural disaster. The expert panel have explored a set of interesting strategic moves for the innovation, adoption and diffusion of emerging technologies to tackle various types of natural disaster. It is essential to innovate dominant design of intelligent systems, machines and tools at optimal cost. Most of the technologies are at emergence phase of S-curve. The expertpanel are analyzing strategy of emerging technology innovation in terms of R&D policy, learning curve, SWOT analysis, technology life- cycle analysis and knowledge management. An intelligent R&D policy should be defined in terms of shared vision, goal, strategic alliance, collaborative, collective and business intelligence. Top technological innovations are closely associated with various strategies of learning and knowledge management, more specifically creation, storage, transfer and intelligent application of knowledge. It is essential to analyze strength, weakness, opportunities, threats, technological trajectories, technology diffusion and dominant design of this innovation today.
Rain plays an important role in global economy and the yield of agriculture. But, it is a natural phenomenon and it does not fall as and when we needs it. Triggering rain on demand is an old dream of mankind, with a huge potential socio-economical benefit. It is an interesting research agenda to do SWOT analysis on various methods of artificial rainfall. Traditionally, artificial rainfall is created through cloud seeding method by spraying different chemicals such as silver iodide, calcium chloride or sodium chloride from the aircrafts in the cloud region. Nucleation starts on these chemicals, which lead to the precipitation and then rain. This process has been experimented in South Africa, Thailand, Japan, Mexico, Brazil and some parts of India. The reliability and consistency of the method is low; the risk of failure is high; the cost is also high; it may have negative impact on human society, plants, animals and nature from the perspective of environmental pollution since sprayed chemicals come to the earth along with the rain. Laser induced rainfall is comparatively more economical and reliable method having less pollution and applicable to both white and black clouds. But it is a new method based on the research that self-guided ionized filaments generated by ultra-short laser pulses are able to induce water-cloud condensation in the free, sub-saturated atmosphere at altitude between 45 and 75 m. In this method, a high power pulse laser creates a bunch of filaments or low resistance path between lightning cloud and the earth.
The fifth element of deep analytics is strategy. This element can be analyzed from different dimensions such as R&D policy, shared vision and goal, learning curve, technology life-cycle analysis, technology diffusion and knowledge management strategy. At present, the technology of artificial rainfall is at emergence phase of S- curve. We need fast diffusion of this technology globally to fight against flood and droughts. It is possible to explore different strategic moves for efficient water management; this is basically a natural resource planning (NRP).
Save water bodies : It is essential to adopt multi-dimensional strategies to save existing water bodies such as intelligent and rational capacity utilization of water from both artificial and natural rainfall; efficient water storage in lakes, ponds, reservoirs, water distribution channels and canals; desalination of sea water; restrict wastage of water in swimming pools, water parks, luxurious use of air conditioners and air coolers, by the rich and super rich classes; tap at roadside and leakage from pipelines; conservation of water to tackle flood and drought, water pollution control (e.g. tube well equipped with water purifier, filter at pumping stations), cleaning of drainage system and riverbed deepening, mutual agreement and dialogue, restriction of illegal encroachment of water bodies, dredging of rivers or canals, collaborative planning, forecasting and replenishment and banning restriction on natural flow of water in river, canals, seas and ocean across borders or boundaries.
Demand & supply management: It is essential to estimate the gap between demand and supply of water for a specific zone (e.g. district, state, country). The demand plan is estimated considering various application domains such as agriculture, industries (e.g. manufacturing plants, retail outlets, life-science industry), construction projects, energy (e.g. power plants), drinking water consumption (e.g. mineral water, fruit juice, beverages, soft drinks), cooking food, washing and cleaning of bodies, garments and cars, religious and cultural events (e.g. marriage, parties), entertainment (e.g. swimming pool, sports and games events, infrastructure and ground maintenance), service sector (e.g. education institutes, student’s hostels, healthcare institutes, hospitals, offices of private and public sectors, banks and financial services, communication, IT firms, travel and hospitalities, hotels, restaurants) and miscellaneous purposes like transport and logistics services, workshops, seminars, conferences, administration and governance. The supply plan is estimated based on real-time data on natural and artificial rainfall, inflow and outflow of water in a river, availability of water in the reservoirs, wastage or loss due to pollution and disposal of water through drainage system.
Collaborative intelligence: Let us first explain the problem of resource allocation and sharing among multiple entities. It is basically a problem of supply chain management. Let us first consider the concept of supply chain in manufacturing sector. Then, the concept can be extended to river water sharing mechanism. Typically, a supply chain is a network of organizations that satisfies the demand of ultimate customers by producing values in the form of products and services. Supply chain management is a novel management paradigm; the basic objective is to improve the competitiveness of the supply chain and to fulfill ultimate customer demands by integrating a network of organizational units through systematic coordination of material, information and financial flows. A supply chain includes all the stages involved directly or indirectly in a business process - suppliers, manufacturers, distributors and customers. Each stage performs different processes and interacts with other stages of the supply chain; there is a flow of material, information and funds between different stages. The ultimate objective is to maximize the value, which is measured in terms of the difference between revenue generated from the customer and. the overall cost across the supply chain. In case of river water sharing, a supply chain is a network of upstream and downstream states or countries that satisfies the demand of water of consumers (e.g. agriculture, industrial plants, common people). It is essential to integrate and coordinate the flow of water among various entities through appropriate infrastructure such as distribution channels, irrigation system, dams, storage and drainage system.
Integration of organizational units and coordination of flows of material, information and funds are the basic building blocks of supply chain management. A lack of coordination occurs if information is distorted as it moves across the supply chain or if different stages of the supply chain focus on optimizing their local objectives. The phenomenon in which demand variability is amplified as one moves up the supply chain is known as Bullwhip effect. There are five main causes of Bullwhip effect – error in demand forecasting, high lead-time, batch ordering, supply shortage and price variations. This problem moves the partners of the supply chain away from the efficient frontier and results in a decrease of profitability and quality of service. It is essential to define frameworks for tighter integration and improved coordination of business processes along the supply chain. Successful integration depends on three factors - choice of partners, inter-organizational collaboration and leadership. Effective use of information and communication technology, integration of advanced planning system and enterprise resource planning (ERP) system and process orientation ensure improved coordination of flows in the supply chain. There are various domains of resource allocation in real world such as river water sharing among various states or countries, bandwidth allocation in communication sector, energy flow in a smart grid, budget allocation and typical supply chain management in manufacturing and retail industry. Let us explore how to extend the aforesaid concept of supply chain management to river water sharing between upstream and downstream states. In case of river water sharing, a lack of coordination and disputes occur if information is distorted as it moves across the supply chain or if different stages of the supply chain focus on optimizing their local objectives of demand and capacity utilization. For example, an upstream state may be reluctant to share water with the downstream state.
Collaborative intelligence is an emerging field of artificial intelligence which is focused on human computer collaboration. It is the basic building block of the proposed resource sharing mechanism. Let us first define collaborative intelligence. It supports supply chain collaboration. Collaborative planning, forecasting and replenishment (CPFR) is a strategic tool for comprehensive value chain management of an organization; this is an initiative among all the stakeholders of the supply chain in order to improve their relationship through jointly managed planning, process and shared information [4]. The ultimate goal is to improve a firm’s position in the competitive market and the optimization of its own value chain in terms of optimal inventory, improved sales, higher precision of forecast, reduced cost and improved reaction time to customer demands. Information technology allows supply chain partners to interconnect, but trust is also important. The interplay between trust and technology encourages the commitment of collaboration among the organizations. The partners of a supply chain are often reluctant to share their private information. What has remained the open issue is how privacy can be ensured in exchange of strategic information for collaborative supply chain planning. In case of river water sharing, supply chain collaboration is essential for efficient demand and supply management.
Collaborative intelligence is achieved through multi-party negotiation. Negotiation is a means for a group of decision-making agents to reach mutually beneficial agreements through communication and compromise. It is an important conflict management and group decision-making technique by which a joint decision is made by the agents who cannot achieve their objectives through unilateral actions. They exchange information in the form of offers, counter-offers and arguments and search for a consensus. A wise agreement resolves the conflicting interests of the community fairly and is durable. Negotiation methodology has two key components – negotiation process and negotiation protocol. Multi-party negotiation is a group decision-making process having five distinct phases. The negotiation process starts with the planning phase. The agents initiate several joint activities by specifying their objectives, preference, aspiration and reservation levels and communication mode. Next, they set various agenda such as negotiation protocol, the timing of exchange, deadline, priorities and constraints. Then, they exchange offers and arguments; learn about the limitations of other agents; identify the areas of agreement and disagreement and modify negotiation strategies. Next, they develop joint proposals by relaxing their individual limitations and reach an agreement. Finally, the agents analyze the compromise proposals at conclusion phase and may explore the scope of possible improvements.
The negotiation protocol is a formal model which defines a set of rules to govern the processing of a negotiation support system and related communication and specifies permissible inputs, assumptions, actions and constraints. A protocol can be evaluated on the basis of different perspectives such as computational efficiency, communication efficiency, individual rationality, distribution of computation and pareto efficiency. Distribution of computation is necessary to avoid the problem of a single point of failure. An efficient negotiation mechanism enables the agents to reach a Pareto optimal solution by decreasing the cost of negotiation.
Negotiators are the decision-making agents involved in the negotiation process; the other interveners are mediator, arbitrator, facilitator and rules manipulators. The mediator acts as an impartial agent and guides the negotiators to reach an agreement. The arbitrator may generate a solution on the basis of facts and arguments; the rules manipulator can alter the rules of the negotiation.
Collaborative intelligence in resource allocation is associated with efficient collaborative supply chain planning. Planning is defined as a rational, structured decision making process which aims to find the best choice of objectives and measures to a decision situation and its environmental setting. The coordination of operations along the supply chain requires well structured planning processes. In case of collaborative supply chain planning, two or more local planning domains collaborate through sharing of relevant information in order to create a common and mutually agreed upon plan. It has five strategic moves - domain planning, data exchange, negotiation & exception handling, execution and performance measurement.
Collaborative intelligence is associated with efficient and intelligent supply chain contract such as swing option. Swing option is a specific type of supply contract in trading of stochastic demand of a resource. It gives the owner of the swing option the right to change the required delivery of resources through short time notice. It gives the owner of the swing option multiple exercise rights at many different time horizons with exercise amounts on a continuous scale. A typical swing option is defined by a set of characteristics and constraints. There are predefined exercise times ti, i
[1,2,..,n], 1≤ t1
t2…tn≤ T at which a fixed volume of d0 units of computational resources may be obtained. With a notice of specific short period, the owner of the option may use swing right to receive more (up-swing) or less (down- swing) than d0 at any of n moments. The scheme permits swing only at g out of possible n time moments where g ≤ n is swing number constraint. A freeze time constraint forbids swings within short interval of the moments. The local constraints up-swing [
] and down-swing limits [
] define how much the requested demand di at time ti may differ from d0. There are two global constraints which restrict the total requested volume D within the contract period by maximum total demand (
) and minimum total demand (
). The option holder must pay penalty determined by a function 
for violating local or global constraints. The next section outlines Resource Sharing Mechanism (RSM) based on collaborative intelligence and then applies the concept to a test case of river water sharing dispute.
5.1 Case Study – Wild Bushfire
Prof. Bush and Prof. Alan Border are discussing the following case study. Is it possible to validate the rationality of various strategic moves to control wild bushfire globally? Is it possible to extend this study to tackle the disaster of volcano also?
There was a wild bushfire in Astralia in December’2019 - 28 people dead; 3000 animals dead; is it not a natural disaster and emergency catastrophe? Is it possible to exercise a crazy, wild brainstorming session on the above globally and adopt a multi-objective set of moves to tackle the fire so hot so big so dangerous so awful?
Laser induced rainfall
Cloud seeding using the concept of cloud physics
Artificial increase of humidity of air
Is it possible to divert direction of strong wind causing fast spreading of bushfire?
Is it possible to deploy real-time sense-and-respond system for automated smoke detection?
Prediction of wild bushfire : is it possible through broadcast, satellite and mobile communication system (e.g. RFID. GPS)?
Multi-party collaborative resource sharing in terms of man, machine, material, method and money for automated fire extinguishing system (e.g. spraying CO2, foam etc.)
Design of fire-proof houses having sufficient distance from forests, storage facilities for harvesting rain and ground water, avoiding combustible building materials such as wood, coal and paper, equipped with effective fire extinguishing system, use of solar water pumps, emergency exit passage.....
Call Threat Analytics :
o Is it a natural disaster caused by the friction between branches of trees and strong wind?
o Lightning strike – lightning arrester, cactus plants;
o Is it a manmade disaster due to use of fossil fuel by tribal people (e.g. coal, diesel, petrol, fireworks) beside forest, bushes and wood?
o Is it an act of bio-terrorism (refer: Amazon forest fire in 2019 for exploration of oil and gas)?
o Effects :
5.2 Case Study – Epidemic & Pandemic
Dr. Han and Dr. Gatting are analyzing the following case study. Is it possible to adopt a set of intelligent strategic moves rationally to fight against epidemic and pandemic outbreak globally? The basic objective is to develop an artificial immune system. The objective of the strategic moves is not to create any unnecessary panic. Rather, we need a rational, optimal mix of proactive and reactive or adaptive approaches for epidemic control in time. It is essential to formulate an intelligent and rational global security policy.
Use alternative workplace and work from home.
Block supply chain (e.g. food chain, retail chain);
Block HR chain
Social distancing : which is correct practice – social distancing or physical distancing?
Contact isolation (e.g. man to man, man to animals), pressure isolation, use of masks, /* use of masks for long duration may result respiratory problems as individuals intake CO2, the byproduct of their own respiration */
Socially responsible initiatives: socially etiquette and responsible behavior: hand shaking, coughing and sneezing, use of handkerchiefs and shoes; Precautions in washing raw meat and cooking meat (e.g. beef, chicken, pork, mutton, cockroaches, snakes, pangolins); restrict spitting on roadside, use of UV light inside room;
Quarantine of virus infected agents in special camps;
Border seal between neighboring countries;
Restriction on logistics i.e. transport through surface (e.g. car, bus, truck, train, metro rail), water (e.g. ship, steamer, boat) and air (e.g. plane, chopper, helicopter);
Flaws in scanning and detection of infection by thermal scanners at ports and air ports:
Develop AIS (Artificial Immu