Part 2. – Increasing the Return on Investment – a holistic view on benefits from digitalization

Continuing from where we finished in the first part, Decreasing Maintenance Costs, of this blog series on “Why should CFO’s in industrial companies be all over edge computing?”, in this part 2, I want to look at the benefits more from a holistic view by including both some balance sheet line items as well some indirect benefits.

Decreasing maintenance costs is a business case already big enough to get every CFO interested in edge computing and digitalization. This includes not only the industrial assets like rotating machines themselves, but also, and maybe above all, the processes that surround them. These processes, such as Maintenance and Operations or Asset Life Cycle Management, are seriously outdated and have fallen way behind similar processes in other industries where new technology has been used to disrupt old ways of doing things, for example vehicle fleet management or information technology, not to mention the consumer side where our entire lives rotate around various apps and platforms. According to Deloitte, poor maintenance strategies can reduce a plant’s overall productive capacity between 5 and 20%. Recent studies also show that unplanned downtime costs industrial manufacturers an estimated 50 B$ each year.

To see the impact of these new technologies, we can approach the benefits by looking simply at a Du Pont formula or the balance sheet and map the changes from moving to a remote condition monitoring system to the components of each formula. Naturally the impacted line items vary case by case, but at a high level some of these could include the following:

New sales and new business model opportunities from understanding how an asset is really being used, what condition it is in, when to offer service, training or other additional services and when consumables and/or parts that wear need attention – this translates into customer intimacy – having the tools to be truly close to the customer, in a true partnership. There are several examples of new revenue streams, ranging from new services, like training, to selling for example filters, not based on time but by how clogged they are.

Taking it one step further, by having this level of information, it is possible to introduce new business models, sell compressed air as a service, torque as a service and so on. These new business models are built on information, full transparency on the asset generating the service and both its cost- and revenue drivers. Not selling assets, but services, has implications on the balance sheet, cash flow and working capital to single out a few.

If the asset is maintained properly and not run to fault, how does this translate into financial numbers? In addition to the cost implications, outlined in the first part of this blog series, there are several direct areas of impact on the balance sheet. Longer asset life means less capital investments and higher ROA. It also means better resale or residual value. Longer asset life also translates into less interruption to the process as there are less installations of new assets. Higher utilization of assets and respectively higher uptime of the process are naturally the ultimate goal.

These are not just groundless promises. It is simple mathematics. The quality of the information, cost and results of implementing these systems can be easily quantified and verified. And have been, as mentioned in my previous blog on decreasing maintenance costs. The concept is straightforward and easy to understand. We can use our own healthcare as an analogy. Is it better for the body and mind as well as for the wallet to maintain a healthy body or to simply deal with it when sick, missing work and paying for expensive hospital time? With machine health, exactly the same principle of preventative maintenance applies. Only now, with edge-computing coupled with the cloud, the transparency has been taken to a totally new level at a radically lower cost.

From a financial perspective, choosing a condition monitoring system can be tricky – the solutions vary greatly in features and functions as well architecture. The more manual “components” the system and the process supporting it has, the more expensive it is. Using legacy components with less than optimal interfaces and firmware add cost and reduce scalability. The more interfaces there are, not only the more expensive it is, but the more expensive it will be to maintain, grow and add new functionality to. The more integrated it is from user interface (UI) to sensor, the better. Point-to-point systems, systems built around PLC’s and on-site fixed systems can deliver great local value, but they are not scalable – no economies of scale nor scope. The most agile systems can be commissioned in days and scale up without limits.

The new business models and architectures allow a fast and flexible way to implement new systems. When the data transfer relies on mobile technologies, there is no need to penetrate fire walls and integrate the system at the local level to the IT-infrastructure. The sensors can be often attached without stopping the process and due to the fully integrated architecture, commissioning is done in days. Standardized but agile solutions are scalable and can be used to monitor numerous types of assets simply by choosing the respective sensors accordingly.

The business model is simple. The smart units, edge-computing devices, have a unit price and the data transfer, user interface and analysis components are charged on a monthly subscription fee base. Naturally the entire system can be subscribed on a monthly fee as well, including hardware and the cloud offering. Easy to budget and easy to scale up.

Data collection with the intention to only process it further in the cloud will come back to haunt you. Sophisticated vibration monitoring tools, that are the basis for understanding machine health, generate giga bytes of data every day. Moving that amount of data around from numerous assets is prohibitively expensive but also unnecessary. Edge computing is a must here. Embedded algorithms that can be updated and modified from the cloud process the data at the edge, at the asset level, into smart data before transferring only a carefully chosen amount of smart data to the cloud. A scalable, fast-to-deploy, pay-as-you-grow architecture is key.

At the end of the day, it is the information you are interested in, not the infrastructure.

Below are some benefits from Part 1 as a refresher to think about, and to map back to the Balance Sheet and ROI calculations.

As a final thought, digitalization of assets with condition monitoring solutions is easy to pilot. A proof of concept, or POC, can easily demonstrate the financial impact of these new technologies. “Fire bullets, then cannonballs “, as Jim Collins put it. A worthwhile opportunity for all CFO’s to revamp the financials around industrial processes.

1. Transparency. Establishing an 24/7 “umbilical cord” to assets. A source of information to facilitate design and innovation both in technology and business modeling.
2. Continuous Improvement. Through direct access to the assets, how they perform and how they are being used, continuous adjustments are possible.
3. Asset Management. Managing the life cycle of each asset. Knowing what you own and what shape it is in. Extending the life.
4. Optimizing the performance and uptime of assets.
5. Maintenance. Enabling the evolution from reactive to preventive to predictive maintenance. Reducing direct labor, driving times of mobile crews, simplifying logistics, knowing what spare parts are needed etc.
6. Safety and Training. By learning from how the machines are used, serviced and handled, the operator can benefit from focusing training on the relevant areas in order to increase productivity, safety and the life span of the machines.
7. Performance. Thanks to continuous and comparable data – relevant key performance indicators can be built for each asset and process.
8. Modernization. Turning “dumb” machines into intelligent by retrofitting them with intelligent devices.
9. Customer centric design. By understanding how the asset is really used in the customers environment, the R&D organization can better design products from the customer perspective.
10. Data availability. Today the data is trapped in the head of the service engineers or their laptops. Modern tools and the architectures they are built with, make data available for everyone in the organization to benefit from, from O&M to sales to finance.
11. Sustainability and Circularity. Understand the carbon footprint, emissions, energy use and life of an asset.