Industry 4.0 - Monetizing Data

Many manufacturers are not considering a connected devices strategy because they don't want to become a software company. This should not be a concern, as there are a number of strategic options they can pursue.

1.      Data as a raw material

Not every manufacturer will have the resources or customer base to justify building out a comprehensive connected product strategy and related software solutions. But every manufacturer has the potential to collect data from their customers and there are a number of options for monetizing anonymized data:

• There is a growing number of data markets that make it possible to monetize the data, such as #Datarade, #Snowflake Data Exchange and #AWS Data Exchange;
• Anonymizing the data and selling it to companies that are building out solutions, such as systems integrators, 3rd party software vendors, large customers that are developing their own internal solutions;
• Partner with other manufacturers that have complementary devices, pooling the data to create more value.

2.      Analytics

The next step in the value chain is to do something with the data. Some of the most common uses are remote monitoring, condition monitoring, predictive maintenance for your equipment. This can be done internally using a company’s own development resources; bringing in a systems integrator to build out the analytics; or licensing pre-built solutions.

And this is a good time to point out that manufacturers do not have to “become software companies”, but they will need to add software to their business model. There have been a number of good discussions about this on LinkedIn, and the challenge is not developing the analytics programs. The challenge is how to create the right business model and organization to sell these offerings. 

The further up the value chain a company moves, the more important it will be to understand how to sell and support the solutions through a dedicated structure.

3.      Applications and solutions

Collecting data and understanding how to do analytics lays the foundation for building out applications and packaged solutions. 

The distinction between “analytics” and “applications” might seem a bit fuzzy. I think of analytics as being device-specific, for example, monitoring a piece of equipment to calculate the remaining life, identifying anomalies, or getting a better idea of when to schedule the next service call. Applications are packaged solutions that can be sold on a repeatable basis to a wide range of customers. Some of the functionality may be the same, but there is a difference in how the solutions are architected and sold to their customers.

Building out applications that leverage the data is an effective way to:

• Make customer relationships stickier;
• Generate new sources of revenue;
• Gain entry into accounts that are using competitive devices;
• Monetize the investment in data collection.

4. Managed service

This is where I believe manufacturing is headed. Companies will combine the physical devices, connectivity, data collection, analytics, actions and maintenance as an end-to-end managed service. This model will drive faster adoption as it eliminates one of the biggest objections we see from customers - they don’t want to learn how to use software. The managed services model takes a lot of the complexity out of adopting new technology.

This model works particularly well in industries that have consumables, where the rate of consumption can vary widely based on different variables.

In robot welding the consumable is filler metal, the metal that is used for the soldering process. One of the biggest variables is operator behavior, and how much waste they generate based on how they operate their machines – a sloppy operator could be using 20-30% more filler metal than someone that is more careful. As a managed service, a manufacturer could deliver the entire system and reduce the overall operating costs for its customers. The manufacturer makes less money on the filler metal since it is being optimized, but they lock the customer in to using their brand.

In industrial air filtration the consumable is replacement filters. The life of a filter is impacted by temperature, humidity and, most critically, the amount of compressed air that is shot into the filters to dislodge the dust they collect (too much air pressure the membranes break down prematurely; not enough pressure and the filters clog up with dust). All of these can be measured with sensors, and the useful life can be extended. Again, the manufacturer makes less on the consumables if nothing changes, but filters are generic, and it gives the manufacturer an opportunity to not just lock in their own customers, but to monitor dust collectors from their competition and grow market share by providing filters for all of the machines.

Pricing models will vary, but could be a subscription with a fixed monthly or annual payment, or variable pricing based on the actual output – a true outcome-as-a-service model. An example of this is Stihl hand tools. They have developed a power drill that measures the amount of torque that is needed. A customer could rent a drill for a weekend, and they would pay more if they were drilling through concrete, requiring extra torque, than if they are drilling through drywall.

5. Platforms and ecosystems

Becoming a platform is a strategy that a relatively small number of companies can do successfully, and for most manufacturers it isn’t necessary – there are more than enough platforms that they can integrate with and benefit from an existing ecosystem.

Building a platform is a long-term strategy, and the challenge is to develop a business model that:

1. Drives broad adoption of the platform – either you become the standard or you becomes part of someone else’s ecosystem and have to comply with their standards;
2. Generates revenues to i) “train” customers to see the added value they are getting from the technology; ii) fund the cost of sales and marketing to drive adoption; and iii) fund continued development in new solutions;
3. Builds a critical mass of customers that makes the platform viable. The Achilles heel for most platforms is not being able to scale to the point where it becomes attractive for third-parties (customers, systems integrators, other manufacturers to build additional apps and create a network effect;
4. Lays the foundation for accessing, aggregating and monetizing more data from more sources;
5. Creates a barrier to entry for competitors. These competitors can come from many different areas:

• Direct equipment competitors that launch their own platform and want to “own” the same customer base;
• Upstream platform players such as Siemens MindSphere, ABB Ability, PTC, etc. As they expand the footprint for their connected solutions they are likely to look for gaps in specific downstream verticals;
• Your customers. Large, strategic customers may not want to rely on third-party vendors and opt to develop their own platform that you will ultimately need to integrate with. The power dynamic between customer and vendor changes;
• Infrastructure companies such as AWS, Microsoft Azure and Google, which are constantly adding new features and capabilities to their platforms;
• Pure software and analytics companies, such as Tableau, SAP, Oracle, etc.;
• Start-ups, companies delivering platforms and analytics solutions that capture data from existing equipment and legacy software systems.

There are examples of companies that have developed successful platforms, such as #JCI for smart buildings (Open Blue) and #dmgmori for machine tools with CELOS.

Conclusion

Manufacturers should not be discouraged from building connected devices because they do not want to become a software company. They can take a step-by-step approach to building out a longer-term strategy, starting with a low-impact model of collecting and monetizing data from their devices, and moving up the value chain if it makes sense for them to do so.