Cognitive Blockchain?? An Agriculture sector perspective!

–          By Sairam Bollapragada and Rajesh Mohandas

In today’s hyper-connected world which is driven by hyper-dependent technology landscape, black swan effects are necessarily increasing as a result of Volatility, Uncertainty, Complexity and Ambiguity in the given globalization scenario. There is recognition that the demand (crisis?) in food security is only going up. Trust is becoming more a mandate than an option, especially for this sector that focus on “Farm to Fork” while already battling Drought, Emerging crop diseases, Pest resistance to chemicals and genetic traits, Phosphorous mines depleting, Salty soils, Fertilizer dependence and growing influence of anti-science forces.

A bigger threat faced by this $5 trillion sector representing 15% of global consumer spend, 40% employment and 30% greenhouse emission, is the “agro-terrorism” too. In the United States alone, crop and forest production losses from invasive insects and pathogens have been estimated at almost US$40 billion per year.

Hence the need for a “TRUST PROTOCOL” and a ledger of everything to establish transparency and traceability to the sources assisted by cognitive systems, to address the ever increasing concern of providing necessary quality and safe nutrition for a growing population. To accomplish the growing need, the food production should increase by 70% from the current levels (at near zero wastage) and one potential solution to the rescue could be the intelligence driven Blockchain (Cognitive Blockchain?)

This kind of Blockchain can create techniques for  upfront detection of malicious agents in the autonomous AI dominated supply chain. It brings in “Consensus” and “Persistent” algorithms rendering multi-agent Cognitive Connected Solutions into an evolving self-organized structure capable to overcome Data Oligopoly. Let us look at few sample applications:

  1. Transparency related issue resolution:
    1. Fund allocation by Government or private agencies to farmers in developing nations do not reach the intended farmers in time due to various reasons and leads to farmer’s bad debts. Usage of Blockchain based digital tokens as currency can come to the rescue of this scenario where bitcoin-enabled farmers can transact for fertilizers, seeds, and other necessities with least probabilities of being misused or imitated, ensuring the right usage of allocated funds creating maximum needed impact. Furthermore the AI Algorithms can add predictive features to enable the agencies to take proactive measures and plan for the future budgetary allocations.
    2. The above can also be used to stall the misuse of land documents by middleman or land-sharks standing in for the farmers. Blockchain can help create immutable land titles to prove the ownership and insure the farmers from the widespread corruption through the trust and transparency driven by Blockchain. The cognitive techniques can further aid in fighting fraud detection, money laundering, counterfeit currency, etc.
  1. Brokerage Avoidance:

High insurance premiums paid by farmers is a wide known issue, where majority of the play is by the middlemen. Cognitive Blockchain solutions, can help eliminate the middlemen and add the required intelligence where the CPQ algorithms will help farmers configure the insurance plans and opt the lowest premium for their crop produce, avoiding the brokerage/processing fee involved ensuring their premiums are actually paid in time.

In addition, such solutions will help insurance companies to better understand a farmer’s risk profile by predictive modeling, estimated profitability bettering their credit history and making them more creditworthy.

  1. Supply Chain to Demand Chain:

With AI, ML and analytics, the behavior of both the buyer and seller is seeing a change. Blockchain makes it even more interesting with Cognitive demand forecasting. As the appetite to handle more data goes up, the number of input sources and players participating in the demand forecasting will increase. With intelligent Blockchain solutions, one can not only keep track of the transactions and contractual obligations with suppliers and other stakeholders, but also gain visibility into the demand-supply scenarios. The farmers can run queuing algorithms and thus proactively route the supply to predictively meet the right demand in right time, making the shift to the supply chain as demand chain.

  1. The Food Security factor:

Forbes reports that a study conducted at WALLMART that took 6 days and 18+ hours to trace the source of a Mango carton, was completed in less than 3 seconds with Blockchain. Described by the Economist as “the trust machine”, blockchains can provide supply chain transparency and data integrity, allowing a visible assurance of authenticity and assist fighting food fraud, especially, the organic food fraudulent labeling that is becoming prevalent today.

If leveraged effectively, Cognitive Blockchain can play a very critical role in accomplishing the target of safe, quality nutrition needs of 9.6 billion population by 2050!!

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Real Time Supply Chain Analytics

Real Time Supply Chain Analytics

By Sairam Bollapragada & Rajesh Mohandas

Supply chain managers have seen increasing challenges to create, and keep, efficient and effective supply chain methods, Customer Service, Operating Cost Control, Planning and Risk Management, Inventory Control, GTM Speed, Supplier / Partner relationship management, Green Supply Chain and Talent (Resources) are a few burring issues that are on the top of the charts that burn the midnight oil. A survey by McKinsey says the companies who have already engaged in leveraging Digital Technologies have managed key trade-offs on barriers to better performance : raising risk, lack of collaboration and low CEO involvement.

The fall of this decade has seen major shift in the supply demand dynamics, the traditional supply chain solutions are not equipped to handle complex scenarios due to lack of visibility. There is a competitive demand for real-time responsiveness which can be addressed by the combination of Data Science and Emerging Technologies connecting customer service with Social and Mobile platforms that are cloud enabled on one hand and strengthening visibility into operations with IOT based real-time analytics. The icing on the cake is emergence of machine learning which is all set to address the tactical challenges and give signature ready recommendations for decision makers to gain maximum mileage.

Supply chain management will gradually be disrupted by the rising adoption of IoT and advanced analytics.  The challenge faced by the supply chain practitioners and players is inability to take advantage of technology to the fullest extent while they are trying to simultaneously integrate their supply chain systems across a much wider range of information sources due to lack of 360 degree view of both business and customer.

  1. Strategic Planning: The very first component of the supply chain, Strategic Planning, comprises of Strategic supply design and Strategic sourcing. Here real time analytics can be used for Supply Chain alert monitoring and the insights will flow into Long term planning, Bid Management, Contract management, Catalogue management and Source determination, real time information can be accessed by decision makers that are geographically dispersed to take collaborative decision on a cloud enabled mobile application. 
  2. Demand Planning: The Next component of the supply-chain value stream is Demand Planning the three crucial capabilities here are Forecasting, Promotions and Demand Consensus. Advanced real-time analytics help with Macro calculations and planning bill of materials leading to collaborative demand planning and characteristic based forecasting.
  3.  Supply Planning: The heartbeat for any supply chain is the supply planning which comprises of capabilities like Safety stock planning, supply network and outsourcing decisions, Distribution planning, Customer and Supplier collaboration. The best component in the value chain where Emerging technologies can be used with the fullest potential is here, the power of cloud enabled CRM systems and Communities connecting the enterprise giving a 360 degree view to the entire ecosystem including the suppliers, customers, partners and the enterprise following with the power of advanced analytics and big data enabled deep learning algorithms come handy. Some examples where one can leverage advanced real-time analytics are in the area of multi-level supply demand matching, whereas the artificial intelligence neural network algorithms can be plugged into supply network planning.

Procurement, Warehousing and Order Fulfilments are three equally crucial parts of the supply chain operations that are interlinked and often become bottleneck in the supply chain due to lack of visibility. In a connected supply chain environment the intelligent algorithms need to be plugged in here such that all three areas are interconnected and all repetitive processes can be automated through RPA, what with NLP loaded Analytics providing intelligence and insight into the process.

4. Transportation: The last component of the value chain is Transportation. Often the biggest complaint from the players of supply chain is “Visibility to the Tail”. This is already being accomplished by real time analytics, bringing in a predictive model that combines features like load consolidation, intelligent route optimization, carrier selection and shipment trending which are few elements of the Transport planning while the Transport execution can feed in data from the shipping interfaces capable of distance determination services. The last inputs come from the freight-costing component that strengthens the predictive model and the machine learning algorithm continuously churns the data and gives real-time insights for both strategists and operations.

Hence, Analytics working in tandem with Cloud, Mobility, and AI, can play a very critical role to bring in great value add to the Real Time Supply Chain scenarios for all those who embrace and leverage. This is even more critical with markets moving towards a more C2C value chain where the customer experience and expectations are fast changing. Retailers, Warehouses, Suppliers, Logistics, and all the agents in the Supply Chain have to work in an orchestrated mode need to be on their toes to remain competitive and relevant to the market expectations.