All businesses and large-scale organisations need to continually review their core operations if they want to remain competitive and profitable. As many companies have found, failure to adapt to new technologies and changing working practices can result in them rapidly falling behind in key areas of business and limit their ability to deliver products and services that meet the demands of an evolving market.
While most company directors and senior managers are well aware of the need to question all aspects of their business to look for the efficiencies and cost savings that can have a direct impact on their bottom line, finding the time and budget to carry out an in-depth review can be the decision-determining factor against going ahead.
Traditionally an operational review has meant investing significant resources to carry out an analysis of the business-critical, end-to- end processes over an extensive time period and extract the quantifiable data needed to pin-point any problem areas. With the need to potentially analyse millions of data-points from different areas of the business the size of the task can result in such projects being extended over many months, delaying any benefits that accrue from the implementation of any recommended changes.
Xanadata’s big-data analytics platform incorporates the latest parallel processing power and machine learning algorithms needed to extract actionable intelligence from terabytes of unstructured data in hours rather than the days, weeks or months normally required. With a range of reporting options available, including a unique 3D augmented intelligence visualisation of the scanned data, senior managers are provided with a detailed analysis based on quantifiable evidence of where a particular process could be improved for the overall benefit of the business.
Using its advanced AI and machine learning algorithms Xanadata provides granular analysis of the massive data-sets and identifies patterns and behaviours from an array of sources that would otherwise be difficult, if not impossible, to spot using traditional methodologies and limited human processing power. By significantly speeding up the data scanning element of the analytics project, businesses can rapidly reap the benefits of deploying the resultant cost and proficiency improvement changes without the extensive delays associated with typical operational review timescales.
• Stock control
• Factory output statistics
• Warehouse/supply-chain reviews
• Sales/capacity forecasting
• Staffing and resource reviews
• Cost and Efficiency Savings
• Revenue / Profitability
• New market penetration
• Solution Brief
• Case Study
• White Paper