Business Monitoring

This post will try to build and idea on business monitoring through a use case.
Most common BI implementation has focus on monitoring business operations and performance.
They achieve it through following key tools.

1. Reports with aggregation and drill down capabilities.
2. Dashboards with collaboration capabilities.
3. Key Performance Indicators (KPIs) and metrics.
4. Alerts and notifications.

Let’s take a use case to explain it.
Cash flow from customers and overdue balances is a key indicator to monitor in any business. Exceeding average overdue balance over a threshold should trigger an automatic alert to responsible executive.  Executive should be able to get into BI system and analyze the problem and take corrective actions.
Typically, he should be able to get an aggregated summary of the problem and might be interested in getting answers to follow up questions.

• What’s an overdue pattern? For example, how much we receive in a period of 30 days, 60 days and 90 days. 
• If 90 days slot is a problem for him, he might be interested in drilling down to get customer wise, region wise or product wise pattern for 90 days transactions. He should be able to analyze and get insights to narrow down the problem to specific region or customer or may be product. 
• Doing all this analysis by looking on various reports, He may discover a simple reason that specific customer is causing this alert. Hence identifying a problem with a customer.
• It may be bit more complex discovery that his invoices of particular product are being paid in 90 days in specific region by majority of customers. Hence identifying a problem with specific product in particular region.
• He might be interested in quarterly, half yearly and annual patterns. He should be able to compare this year, previous year, this quarter, previous quarter, same quarter previous year etc to understand and discover some patterns indicating root cause.

Once root cause is understood, appropriate corrective actions can be taken for example if a customer is causing this issue, we may reduce the risk by holding further supplies till overdue is cleared. 
Above example is a clear case of business monitoring. Such implementations can also deliver or can be extended to deliver some level of business insights.
Implementing such systems requires a mix of relational and dimensional modeling techniques to model data. These implementations are termed as OLAP (online analytical processing) systems. OLAP implementation gives tremendous capabilities. Some of them are listed below.

1. Calculating across dimensions and across hierarchies.
2. Analyzing trends
3. Drilling up and down through hierarchies
4. Rotating to change the dimensional orientation
5. Forecasting
6. What-if analysis.

OLAP implementations for BI are delivering great for business monitoring. They have been reasonable in delivering Business Insights. But due to performance problems and limitations on amount of data such systems can handle, they has not been able to move beyond that towards Business Optimization, data monetization and business metamorphosis.

Keep reading, Next post will try to cover business insights through a use case.