A platform-enabled ecosystem of partners where interaction takes place in multiple ways and value creation is done through collaboration and co-creation is the ideal means to foster a business relationship. The positive impact generated by such an ecosystem leads to higher KPI values and results in higher dollar value generation and savings. HCL has developed its time-tested framework along with prescriptive analytics for partner ecosystem assessment, building, and management.
As the size of the ecosystem becomes larger, the chances of slippage in any corner of the ecosystem also get higher. Slippages may take the form of wrong certification issues, delivery delays, wrong part delivery, ISV product performance, asset breakdown, incomplete orders, payment delay, pilferages, etc.
It is for the interest of all the partners and its ecosystem that the number of slippages and/or failures should be reduced. Any solution concept which can reduce the number of slippages and failures in the partner ecosystem should always be welcome.
Predictive and prescriptive analytics-based solutions help partners make correct decisions based on analytics-driven outcomes. This enables business users to reconfigure documents or alter any action based on the probability of failures and forecasted slippages and take proactive decisions to improve reliability and performance. This concept should have an interactive and intuitive visual interface to iteratively ask, answer questions, and discover new insights. After a natural disaster like a flood or an earthquake, this concept enables qualitative situational analysis post the disaster and recommends alternate production, sourcing, or logistics options.
Slippage detection can tell any partner in the ecosystem what is the predicted chance of failure if they want to do transactions with other partners for a specific type of transaction. Even the details about the type of failure can also be predicted. Based on this, partners can choose their right counterpart for a specific kind of work.
For example, when placing a purchase order for a specific SKU, an OEM should know the chances of slippage for each supplier. They can then decide accordingly. Any partner in the ecosystem should know what the chance is of getting the correct result from a certification agency for a specific purpose of certification. Partners like OEMs, customers, and suppliers should collectively know what the predicted failure chance for any 3PL is for carrying any specific SKU for a specific shipping address. This way, partners can collectively know each other’s strengths and, accordingly, they can make the right decision in the ecosystem.
The concept can be developed once with the help of prescriptive analytics and then deployed in any part of the partner ecosystem. It can be accommodated in most of the hardware platforms. It is cloud-enabled and is capable of automatically collecting transactional data of partners. It is accompanied by a cloud-enabled visibility platform that ensures the visualization of partner action before prediction and after actionable intelligence.
