Effective and efficient supply chains are essential in industries such as consumer goods, capital equipment and pharmaceuticals.
There has always been a focus on using data and technology to assist companies with projection, forecasting, optimising supply and creating new products. However, companies increasingly must confront challenges with absorbing and applying an overabundance of data. The information needed to draw insights includes internal data such as inventory use patterns and energy usage, details from retailers and distributors on transportation and components, and external data such as the weather. The inability to exploit this data has led to inaccuracies, lagging reaction speed, lost sales and higher costs.
Product companies may be reluctant to improve their existing supply chain partners because of the potential risks involved if a partner is unreliable. Enhanced use of data can determine a company’s competencies, reputation, finances and overall track record. Similarly, retailers and distributors may find it difficult to assess the risks involved in working with product companies.
Artificial Intelligence-based solutions can help supply chain-reliant companies with these challenges. The majority of supply chain management executives whose businesses were using AI said they were able to achieve revenue increases (63%) and cost reductions (61%) as a result of the introduction of the technology, according to a global survey by McKinsey.
BlackSwan Technologies’ ELEMENT™, an AI-enabled, Platform-as-a-Service offering trusted by leading organisations around the world, can help enterprises to:
- search for new suppliers that meet cost, data, service and product requirements
- aggregate demand data from different sources for a single source of truth
- use AI-based tools to automate demand and supply matching
- get a better handle over supplier risk management
Below are examples of supply chain-centric industries and use cases, where deploying and tailoring ELEMENT provides exceptional value.
Supplier discovery and screening
A global view of your market to identify new supplier opportunities
ELEMENT enables product companies to customise an automated discovery engine to identify potential suppliers that fulfil particular needs. Likewise, retailers and distributors can identify potential product companies and partners they can work alongside. The discovery engine can encompass extensive, predefined criteria and success factors to identify viable companies in a matter of minutes. A company profile can be built based on size, sector, required competencies, track record, financial performance and more. This can help an organisation to replace a product’s components with readily available, cheaper, easier-to-process alternatives. The search can be carried out across many regions and languages, using numerous public sources and curated industry databases, without going out to tender.
Intelligent, unified demand/supply matching
A single source of truth to optimise demand/supply alignment
ELEMENT can help product companies, suppliers and retailers that currently do not possess a crystal clear picture of their supply and demand data.
ELEMENT aggregates sales and demand data from different regions, systems and databases to get a common view of the business – or single source of truth – and base all decisions on this high-quality data. ELEMENT records the source of every data point and can even assess the likely accuracy of one data source over another.
Once this foundation is in place, the next step is to feed this data into systems that monitor and autonomously adjust production requests to better match supply with demand. This would involve cross-referencing the amount of inventory in each location and distribution centre, providing supply-chain insights, recommendations and alerts to management.
ELEMENT allows organisations to apply multiple AI techniques to optimisation problems, including machine learning/deep learning models that self-determine the weightings of relevant internal and external factors and uncover nuanced situations that could hinder expected delivery. For example, an automated workflow initiated by extreme weather or abnormal volumes of component malfunctions could trigger optimisation actions. All the data and findings are presented in ELEMENT via high-level data visualisations and supported by deep-dive exploratory capabilities.
Continuous supplier risk management
Strengthened verification and continuous monitoring of suppliers’ situations reduces risk
ELEMENT uses an array of AI approaches, including machine learning and rules-based engines, to vet suppliers and assess the potential risks of working with them – as well as with the other companies with whom they are associated. The information screen includes quantifiable metrics such as financial health, as well as qualitative considerations such as legal actions against them, or adverse media targeting their reputation. As company profiles are verified and enriched with information as time goes on, the evaluation of suppliers is a continuously-refined process. This means companies can have a better grasp over supplier risks and analyse the market as a whole more effectively.
Analytically-Driven Decision Making
Comprehensive incorporation of all available data can optimise processes and increase transparency
ELEMENT can help product companies, retailers and distributors avoid decision-making based on partial information and subjective interpretation.
ELEMENT enables organisations to achieve unified supply-chain knowledge, seamlessly correlating information about projected sales, customers, locations, inventory, components, transportation, past and forecasted weather and more, across all available internal and external resources.
The combination of exhaustive data and automatic identification of all relevant patterns in market behaviour means that enterprises can select partners and optimise processes more rigorously. Analysts can learn and understand how recommendations are formed because of the transparency afforded to them by ELEMENT’s “white box” Knowledge Graph model. Data visualisations enable analysts to quickly identify trends, after which they can deep dive into the analytics.
Feedback loops can be set to recalibrate AI triggering, improve efficiency, decision-making and reduce false-positive events.
ELEMENT can provide similar benefits to any industry with a strong supply chain reliance. It further can incorporate AI and big data into related value chain activities, such as customer segmentation for product planning and marketing, and market/competitive intelligence monitoring.