SAS Review

Our review was written by Michael Burns and published in the CAmagazine in October 2006. Although the atricle is a few years old, it should still provide a good starting point in your evaluation. We will try to provide more up to date review in the near future.

Leading System

n the global market for corporate performance management and business intelligence software, SAS Institute Inc. is unquestionably a leader. With 10,000 employees, 4.5 million users and 40,000 customer sites in 110 countries, the company earned revenue of US$1.74 billion last year. Based in Cary, North Carolina, it has offices throughout the world, including Toronto. It also has the distinction of being the world's largest privately held software company. In the past, SAS competed with companies like Hyperion and Cognos. Today, it also shares the market with some ERP vendors that are bundling CPM components with their systems. So why would anyone want to use multiple products if they could just use one integrated ERP solution?

ERP Connection

Answer: historically, ERP systems have been excellent at transacting data but miserable at transforming it into the knowledge needed for CPM. This has led to the proliferation of Excel as the most widely used tool for decision-making. Excel is highly flexible but error prone, lacks an audit trail for changes, leads to multiple versions of the same information (multiple versions of the truth) and is not up to date. Organizations – especially the larger ones -- had no choice but to turn to CPM vendors. Also, many of the larger organizations have multiple ERP systems and find it more economical to use one CPM system to draw data from all of them.

CPM systems typically offer more CPM functionality than ERP systems do. On the surface, an ERP dashboard might look almost identical to the SAS. But below the surface, SAS offers powerful integration and extraction, transformation and loading. ETL tools are crucial for taking information from one or more databases, transforming it by cleaning out inconsistencies and optimizing it for later analysis, then loading it quickly for use by CPM. For companies with terabytes of data (1 terabyte = 1024 gigabytes or 1 billion or 10004 or 1012 bytes), it’s essential to have ETL tools.

Differentiators

SAS differentiates itself especially when it comes to predictive analytics. This is used to determine the probable outcome of an event, such as future sales of a new product. SAS uses multiple methods to forecast demand for products. These methods can be summarized as 1) time series techniques designed to identify forecast trends and seasonal patterns in data, 2) regression or correlation analysis, which considers external factors (independent variables) and their impact on the forecast (dependent variables) and 3) qualitative overrides based on the judgment, knowledge and business acumen of experienced people.