In today's challenging economic conditions, what company doesn't want to get a better grasp on every aspect of cost control and operations? That's an impetus that naturally leads SAP Supply Chain Management (SCM) customers to consider implementing business intelligence (BI) and analytic capabilities such as Supply Chain Analytics.
But before implementing these tools to achieve success, organizations must get a handle on master data management (MDM) and data governance.
"For most companies, they either have problems with the quality of the data or else the data simply isn't there," said Tim Payne, who is a research director at Gartner.
Implementing MDM forces an organization to implement governance -- clarify who has ownership of specific data, who is responsible for maintaining it, and who is responsible for getting it into a central repository, Payne said.
The plus side of all that work, he said, is that the good governance practices apply equally to operational data and the data that ends up in analytical applications.
The next step is to have some ideas around definitions for metrics and key performance indicators (KPIs).
"If one indicator goes up and another goes down, what does that tell you? Many companies don't really have the framework in place to interpret such information," Payne said. "It's one thing to measure and put in place KPIs, but actually having the right ones and understanding how they link is critical to achieving real results."
Many software packages, including SAP SCM 7.0, do come equipped with metrics, which are usually built around the recommendations of the Supply Chain Council, such as the Supply Chain Operations Reference (SCOR) model.
Most companies will probably start to implement BI by simply monitoring performance, Payne said.
"There are benefits from just getting that visibility," he said. "If you start to get those insights, you can go in and perhaps change inventory settings or lead times in a way that will improve your financial performance."
Fewer companies have achieved a targeted, enterprise-wide framework for analytics. At that level, according to Payne, companies have a wide range of metrics available and are in a position to try to understand the interrelationships among them.
"You have different layers of process down to the functional level in a warehouse or traffic department," he said, "and an integrated framework like SCOR can help provide an end-to-end view."
Those things, in turn, can help you understand "what levers to pull and what lumps to push," he said.
The most sophisticated adopters are performing predictive analytics on and with the data.
"At this level, companies are able to leverage analytics to create a what-if process where they can start to build models to predict different behaviors based on different performance in the past," Payne said.
Although hardly any companies are there today, it is the end state to which those applying BI and analytics should aspire. It allows a company to make structural changes, configure the supply chain and really understand the true drivers of profitability.
Assuming that the organization is ready to implement BI and analytics, adopting SAP SCM 7.0 as a foundation is a good place to start, according to Valerian Harris, vice president of Enterprise Solutions at Patni Americas, a consulting firm. SAP's acquisition of Business Objects means that users now have access to tools such as Crystal Reports.
"There is so much functionality, the product has gotten so vast, it has edged out smaller players," Harris said.
Getting organizational support to implement BI and analytics is a challenge in its own right. Payne warns against the risks of "thinking small," noting that there are many analytical tools available but relatively few have the capability to take you to predictive analytics.
In the case of SAP, what's available, including elements from BusinessObjects, is capable of supporting a higher level of sophistication and wider integration, he said.
Composing a compelling ROI argument for making the financial investment in BI and analytics isn't easy. But overall, doing nothing can be the biggest mistake, according to Manufacturing Insight's Simon Ellis.
"It can be very difficult to come up with solid ROI predictions for these things," he said. "Ultimately, someone just has to say, 'We need to do this.'"