Senwes is a diversified agri-business operating in various provinces. Its activities include production inputs to grain farmers, retail and financing.
Business requirement
At the beginning of 2011, the group invited proposals for a business analysis tool that would give it insight into a range of operating areas, starting with retail.
Martin van Zyl, Senwes general manager - IT, says the group runs a SAP enterprise backbone. It required a business intelligence (BI) solution to be installed on top of SAP Business Warehouse (SBW 7.0).
“We needed a fast implementation cycle, ease of development and use, as well as flexibility, to adapt it to other models. Lastly, we wanted to be self-sufficient and not rely on consultants for ongoing development and enhancements.”
Proof of concept
A proof of concept was commissioned from QlikView partner RIC Consulting (September 2010). The company's target dataset comprised all Senwes' retail sales information, ranging back one year.
Van Zyl says RIC utilising QlikView delivered “unbelievably quick” answers (within three days), providing emphatic proof of the solution's speed of implementation. By comparison, a competitor took two weeks.
Quick to implement
In February 2011, the company purchased a QlikView Enterprise Server with 40 client licences, as well as QlikView's SAP Connector, and gave the go-ahead for RIC to develop a retail solution covering Senwes' 28 stores, each including six profit centres (such as in-store, bulk goods and fuel).
“They wanted a dashboard of retail performance across a range of metrics, including gross and net profit, expenses, stock turn and so forth,” says Helena Korb, strategic director and project consultant at RIC Consulting.
Again, delivery exceeded expectation. Senwes went live with the full retail data model within 15 days (February 2011), but Korb concedes the data had already been rendered analysis-ready by virtue of their prior inclusion in SBW.
Van Zyl says the company got all it wanted, plus the benefit of seeing the outcome and impacts of decisions from QlikView's 'what-if' analysis. This revealed possibilities for further development.
Flexible
“After looking at retail sales from a performance point of view, we also decided to view it from a customer angle. While stock turnover patterns feed into inventory management, it could also inform customer management and marketing campaigns.”
He discloses that, in preparation for large-scale adoption of the solution, the company had sent two SAP consultants on QlikView training. The company was therefore by now skilled enough to continue with further development on its own. “The data model was very flexible, allowing us to change the design to the customer model,” he says.
In addition, users had been trained in-house by the two consultants. “While retail staff were not schooled in drawing queries and reports, QlikView was very easy to get to grips with,” Van Zyl reports.
“QlikView is very intuitive; it works the way our brains work,” adds Korb. “Data associations can be retained thanks to QlikView's in-memory architecture, so when users drill down, they don't have to know data hierarchies.”
Payback
Van Zyl says Senwes has seen (un-quantified) return on investment in the speedy implementation and development of BI data models, their rapid adoption, as well as expedited business decision-making.
“The biggest benefit was the rapid decision-making,” says Van Zyl. “To collate information from SAP into a format that the business can use used to take days. Now it takes minutes.
Future data models
In due course, the retail and customer data models were joined by a grain stock management model, Van Zyl continues. Future data models will include a grain contracts management dashboard and an overall strategy execution dashboard for Senwes.
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