Analytics Decision: Buy or Make Capabilities

Three value drivers of analytics platforms are confidence in vendor, development effort, and platform cost. Discover how software-as-a-service platforms and opensource platforms compare in these categories.

Dan Riley, Analytics Manager, Interstates
Dan Riley, Analytics Manager, Interstates

New software-as-a-service (SaaS) analytics platforms enter the manufacturing industry every year. Each platform has unique value adds, ranging from preferred data types to modeling algorithms and feedback loops. Each platform can solve many data needs in manufacturing. Opensource (OpS) software is emerging with expanding capabilities. OpS platforms offer base functionality at very low to no cost. The choice between SaaS platforms and OpS platforms is a decision of purchasing capabilities versus making capabilities.

Three value drivers of analytics platforms are confidence in vendor, development effort, and platform cost. Consider how SaaS platforms and OpS platforms compare in these categories:

Confidence in vendor
SaaS platforms have more learning resources, more documentation of features, and more support of their products. SaaS platforms generally provide integrator certifications that ensure knowledgeable system integrators. These benefits build confidence in a purchase decision. Clients can rely on their integrators and the platform vendor.

OpS platforms have fewer learning resources and documentation. Resources and documentation may be less organized than that of their larger competitors. Clients lean on the knowledge of the integrator more than the platform vendor.

Value advantage: SaaS platforms

Development effort
SaaS analytics platforms are designed to span industry verticals and layers of industrial control while being marketed as versatile and flexible. To be everything to all verticals and layers is to be nothing specifically to any of those constituents. As a result, large platforms require as much programming as smaller options. A standard implementation factor in the industry is equal to the license costs.

OpS platforms require more development time relative to their license fees, if they have any. This is generally due to fewer standard features of the software. Development with open source platforms may have a slower start because of base feature development.

Value advantage: Even

Cost
Big analytics platforms’ costs vary for a variety of reasons. These reasons can include feature set, tier of service, number of licenses, one-time purchase options and software-as-a-service options. In the past, many vendors offered prices that fit an IT purchase profile. Costs are now being structured or reduced to fit the manufacturing profile. Costs are still high relative to existing software solutions needed to operate a manufacturing plant. For example, Seeq, a time-series data analytics tool, costs $45,000 annually for 20 users. That price is equivalent to FactoryTalk View SE with 20 clients.

OpS platforms can range from cheap to free options. Cost may incur from server resources, but many capable solutions are free. Interstates’ analytics team uses the following free software packages: KNIME, Node-RED and Grafana.

Value advantage: OpS platforms

Discretion is needed to fit the best software solution to the industrial data use case. While big platforms offer powerful features and many support resources, they may not be the right solution all the time. OpS software offer solutions for a range of clients and needs.

This article was originally published in our Current Connections quarterly newsletter. Read the article here.

Dan Riley is the Analytics Manager at InterstatesInc., a certified member of the Control System Integrators Association (CSIA). For more information about Interstates, Inc., visit its profile on the Industrial Automation Exchange.

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