What is Online Analytical Processing (OLAP)?

Below is a continuation of the transcript of a webinar hosted by InetSoft on the topic of OLAP, the basics of what it is and an explanation of some of the technology terms related to, what OLAP's benefits are, and what the choices in OLAP technologies and OLAP tools are. The speaker is Mark Flaherty, CMO at InetSoft.

Mark Flaherty (MF): In terms of a higher level definition of analytical techniques related to processing, there is a common tool or technique called OLAP. OLAP is the acronym for "Online Analytical Processing." The literal meaning of this words is misleading and dates back decades ago to early computing. Nowadays OLAP means being able to cut your data up and aggregate it up into an environment that allows you to do multi-dimensionality analysis.

So this means the ability to look at trends, do time-based analysis along a variety of dimensions. This gives you drill-through or down capabilities. You can expand your data hierarchy so you can look at all different levels of your data. The cube model in the industry has been used for many years and is supported by many vendors. MDX is commonly used to express and query against your OLAP environment. In 2001, there was a standard created for XML for analysis, called XML/A, a new format or a method which you could call MDX using an XML interface.

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Approaches to OLAP

So there are a variety of techniques or approaches to OLAP. We’ll talk about what InetSoft specifically supports in a few minutes. But there are different techniques of multi-dimensional OLAP, which is often called MOLAP for short. This is something that is usually a proprietary cube-based environment. There is also ROLAP, or relational OLAP, which is taking advantage of a relational hierarchy in an RDB, or relational database, to structure your data to do your summarizations and aggregations.

Then there is a combination of both called hybrid OLAP which takes advantages of some of the multidimensional aspects of OLAP, its proprietary-based format, combined with the open-standards ROLAP. This is meant to set a high-level context for OLAP, where it sits, and why it is useful and commonly taken advantage of for analysis.

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What Reports Would an OLAP Server Enable for a Food Distributor?

An Online Analytical Processing (OLAP) server for a food distributor can enable a range of reports and analyses that are essential for optimizing operations, improving efficiency, and making informed business decisions. OLAP technology allows for multidimensional analysis of data, making it particularly valuable for organizations dealing with complex data structures like those in the food distribution industry. Here are some reports that an OLAP server could enable for a food distributor:

1. Sales Performance Analysis:
   • Sales by Product Category: Analyzing sales figures across different product categories to identify top-performing and underperforming items.
   • Sales by Customer Segment: Understanding sales patterns among different customer segments, such as restaurants, retailers, and institutions.
2. Inventory Management:
   • Inventory Levels and Turnover: Monitoring stock levels and inventory turnover rates to optimize the balance between demand and supply.
   • Stockouts and Backorders: Identifying instances of stockouts and analyzing the reasons behind them.
3. Supplier Performance:
   • Supplier Spend Analysis: Analyzing spending patterns with different suppliers to identify cost-saving opportunities and negotiate better terms.
   • Supplier Delivery Performance: Evaluating the reliability and timeliness of supplier deliveries.
4. Product Profitability:
   • Gross Profit Margins by Product: Calculating and analyzing gross profit margins for each product to identify the most profitable items.
   • Contribution Margin Analysis: Understanding the contribution of each product to overall profitability.
5. Customer Analysis:
   • Customer Purchase History: Analyzing the historical purchasing behavior of customers to identify trends and tailor marketing strategies.
   • Customer Segmentation Analysis: Segmenting customers based on various criteria (e.g., size, location, industry) to create targeted marketing and sales approaches.
6. Route Optimization:
   • Delivery Route Efficiency: Analyzing delivery routes and optimizing them for efficiency and cost-effectiveness.
   • Fuel Consumption Analysis: Monitoring fuel consumption and optimizing routes to reduce transportation costs.
7. Quality Control:
   • Product Quality Analysis: Monitoring and analyzing reports of product quality issues to take corrective actions.
   • Supplier Compliance Metrics: Ensuring that suppliers meet quality standards and compliance requirements.
8. Promotion Effectiveness:
   • Promotion ROI: Evaluating the return on investment for promotional activities to optimize future marketing strategies.
   • Promotional Sales Analysis: Understanding the impact of promotions on sales for different products.
9. Forecasting and Demand Planning:
   • Demand Forecast Accuracy: Assessing the accuracy of demand forecasts to improve inventory planning.
   • Seasonal Demand Analysis: Identifying and preparing for seasonal fluctuations in demand.
10. Financial Reporting:
    • Profit and Loss Statements: Generating financial reports to understand the overall financial health of the business.
    • Budget vs. Actuals: Comparing budgeted figures with actual financial performance to identify variances.
11. Compliance Reporting:
    • Regulatory Compliance Reports: Ensuring compliance with food safety regulations and reporting requirements.
12. Operational Efficiency:
    • Order Fulfillment Efficiency: Analyzing order fulfillment times and optimizing processes to enhance operational efficiency.
    • Warehouse Space Utilization: Monitoring warehouse space usage and optimizing layout for efficiency.
13. Market Trends and Analysis:
    • Market Share Analysis: Understanding the distributor's market share and identifying opportunities for growth.
    • Competitor Analysis: Analyzing the performance and strategies of competitors in the market.
14. Customer Service Metrics:
    • Order Accuracy Rates: Monitoring the accuracy of order fulfillment to enhance customer satisfaction.
    • Customer Service Response Time: Analyzing response times to customer inquiries or issues.
15. Traceability and Recall Reporting:
    • Product Traceability Reports: Ensuring the ability to trace products throughout the supply chain for quality control and recall purposes.
16. Sustainability Metrics:
    • Environmental Impact Analysis: Measuring and reporting on the environmental impact of distribution operations.
    • Waste Reduction Initiatives: Analyzing and optimizing efforts to reduce waste in the supply chain.