Decision making is always aided by good data. Companies collect data from an ever-expanding number of sources. Nothing wrong with that.
Unfortunately for many companies, making sense of all those data and presenting them to business decision makers are much more difficult tasks than simply collecting and storing them. Older business intelligence tools bought over the years and installed on premises often don’t have new data connections to newer data storage technologies even to begin the process.
Simply looking for on-premises advanced analytics solutions is typically beyond the technical capabilities of most companies’ current staff. In addition, the setup and configuration take a long time before any real, meaningful analysis is even undertaken.
Justifying a cloud service for advanced analytics is an easier sell internally for most companies. Start small is a good mantra, but there must be some meaningful use cases and benefits analysts can use to get management to pay. First, assume that there will be a connection to the on-premises enterprise resource planning (ERP) system because, without the context of products, customers, and sales, most of the other data analyzed lack context for business people.
Here are five common ways cloud analytics improves on-premises ERP software. Admittedly, companies can do some of these tasks with on-premises advanced analytics solutions integrated with the on-premises ERP software, but all are easier and quicker to start when you use a cloud service. These examples aren’t exhaustive, of course, but they are common across industries and in companies small to large.
Sales forecasting is mostly guesswork at least for many companies. It’s educated guesswork but still based more on opinion than numerical facts.
Cloud analytics can assess data collected over several years to arrive at fact-based trends. More precisely, the advanced analytics algorithms look at the on premises ERP data to chart trends not just for product categories but for individual items, including seasonality. Cloud analytics services can then send the prediction back to the on-premises ERP software to fine-tune production planning or vendor order schedules.
People and companies like to group things into categories. It’s just easier to think about groups than individuals. So, a common analytics endeavor is to group customers to make analysis and planning easier.
Cloud based analytics for customer segmentation looks at order history and payment patterns of customers as stored in the ERP database. Bring in more demographic data from the customer relationship management system or other data sources, and cloud analytics generates meaningful customer segmentation using man different characteristics.
Many smart products are capable of sending sensor and location data into the company’s data center when internal IT staff have defined the data flow and storage rules. This is essentially how the Internet of Things (IoT) works. A cloud analytics system gives companies an option to work with IoT data because part of the service is to receive and store the data without needing to set up internal servers. Having all the new IoT data elements available doesn’t help people know what to do with it, though. Cloud services merge product and customer data from the ERP system to provide context for the IoT data nothing more, nothing less.
Supply chain is a fluid term. Cloud analytics has the potential to unite data from vendors and customers in a way that companies dream of but rarely realize. Using a cloud system, partners in the supply chain share with a trusted service data that had been available only in individual companies’ on premises ERP systems. The result is much better visibility into product movement, location, and performance.
Few want to talk about it, but smart sensors allow for more precise tracking of employee location and activities. Storing these data internally is often problematic. It’s much better to say to all employees that the company uses a cloud service. Combining the cloud stored employee activity information with ERP data renders much better accounting data for real costs relative to product, department, location, customer, and so on.