Intelligent Knowledge Management for Livestock Sales

Optimizing organizational knowledge to maximize business outcomes

The global livestock industry is now estimated to be worth ~ $450B. This is up from ~$350B in 2020. The industry is expected to top $700B by 2030. This growth has presented new challenges for the industry as companies struggle to cope with increased volumes of transactions, market disparities, and pricing volatility. The continued reliance on legacy, non-digitized, information management solutions has exacerbated the problem.

Current Challenge

Many existing information management solutions were deployed to support livestock industry conditions that existed two or three decades ago. Those solutions tend to be more analog in nature, inflexible in design, and self-limiting in capability. These shortcomings create several operational and business disadvantages.

Inefficient knowledge retrieval: Slow access to stored knowledge results in missed opportunities and/or non-optimal actions.
Inability to automatically segment data by region creates additional work burdens and increases potential for errors in regional business assessments.
Loss of tacit knowledge due to employee turnover often results in permanent loss of critical information.
Manually activated processes rely on human touch points that are prone to error and inefficient in execution.
Lack of natural language processing (NLP) capabilities restricts the ability to analyze large volumes of textual data to glean valuable insights into customer and market trends.

Legacy Knowledge Management

The Solution – Intelligent Knowledge Management

Plasma delivers intelligent Knowledge Management Systems (KMS) tailored for the specific needs of the livestock industry; KMS that enable organizations to improve internal efficiencies, maximize knowledge utilization and retention, improve market response times and drive revenue growth.

Key capabilities of Plasma’s intelligent KMS:

Rapid Knowledge Retrieval
- AI-enabled knowledge search and discovery
- Rapid access and retrieval of current and historical information
- Roles and permissions-based access to sensitive data
Knowledge Retention
- Tacit knowledge retention despite employee turnover
- Efficient and cost-effective storage of critical operational data
- Self-learning algorithms that provide hardened protection of stored information
Intelligent Workflows
- AI-enabled workflows for data collection, analysis, and action
- Automated decision-making based on perpetual self-learning
- Reduction in the number of human touchpoints reduces risk for error and improves security
NLP
- Automated mining of unstructured data for hidden insights
- Provision of customer service that is faster and more precise
Predictive Analytics
- Recursive data analysis to predict upcoming trends and potential problems
- Proactive vs reactive use of knowledge acquired by the enterprise
- Extension of visibility horizon for competitive advantage

The Intelligent KMS Impact on the Livestock Industry

Business/Operational Impact

	Problem	Solution Impact
Knowledge Retention	Loss of organizational knowledge due to employee and system turnover	AI-enabled collection and storage of knowledge for permanent availability
Knowledge Retrieval	Delayed access to data creates slow reaction to fast-moving business opportunities	AI-enabled rapid search and discovery of information needed to support decisions and actions
Market Insights	Inability to maintain real-time contact with rapidly changing livestock market conditions	NLP technology provides large scale market insights based on recursive analysis of textual content
Process Workflows	Legacy workflow solutions that require human intervention and that do no evolve	Automated intelligent workflows that learn and evolve to maintain maximum efficiency and accuracy
Predictive Intelligence	Inability to accurately predict market conditions and decision impacts	Self-learning algorithms that utilize current and historical data to predict future market conditions