Predictive Maintenance opens new doors to stand out from the market

Many machine manufacturers face the challenge of stagnating, highly competitive markets and decreasing margins for its spare parts. Obviously, markets change, so do the customer expectations. Due to globalization and the growing number of low-price-competitors with comparable products, machine manufacturers need to find new ways of doing their business differently and to differentiate from the market with its unique services.

Therefore, new business models and ideas are needed, as they open new opportunities and challenge status-quo. With technologies such as Predictive Maintenance, new business models can be created. Based on machine data, machine manufacturers learn more about the performance and behavior of their machines and its components.

Therefore, new knowledge will be generated, which can be actively used to improve products, detect customer needs ahead and change from reactive to proactive customer service. In other words: Predictive Maintenance makes visible what was previously invisible and allows the machine manufacturer to recognize at an early stage what his customer needs.

New ways of doing business based on Predictive Maintenance

How can machine manufacturers benefit from machine data and the knowledge generated by Predictive Maintenance? Here are some examples:

New revenue streams

Instead of selling machines with a one-time revenue you are selling the result of the machine´s work and invoice it monthly. (e.g. based on volume, pieces, tons conveyed)

Just-in-time delivery

Knowing the runtime and wear of the machine offers the opportunity to deliver on-time wear / spare parts and related services, triggered by the available online information about the condition of the machine.

These new business models have the potential to change the way business is done. Provided, the end-user accepts access to the machine data, it will create a bonding for a true partnership with benefits for both parties. In our previous articles, we talked about system architecture, sensors, IoT technology and data quality. These are important elements of a Predictive Maintenance Solution and engineers like to elaborate on this aspect with good reason. If we chose the wrong sensor, an unreliable edge device or an underperforming algorithm, the solution will not be satisfying. Yes, these elements are the backbone of success!

However, we have seen that introducing IoT based business models does not only require mastering the related technologies but as well managing the required changes at the machine builder´s organization and its business processes.

Paperboy? Customers expect more!
Change your organization to improve your business.

Imagine you are a machine manufacturer selling easy to install machines. Spare and wear parts for your machines are available from several suppliers. Your machine sales are doing well and if you are lucky, customers even come back to buy spare parts. However, sales are not growing, and you wonder if your after-sales business can´t do better.

Your current business may be similar to that of a paperboy, who is throwing the newspaper over the fence to the front door, not worrying what happens to it afterwards. Now you decide to enhance your machines with IoT and Predictive Maintenance functions, allowing to receive machine data to enhance customer experience during machine operation.

Paperboy? Customers expect more! Change your organization to improve your business.

While in the past, the job was done with the machine delivery (the newspaper at the front door), the job will continue now including the operation of the machine. To be successful with the new approach, it will require attention and change in all steps of your business process.

  • Your sales team must understand the value proposition and being able to explain it to the customers, too. There are many possible obstacles which come along with this new technology like questions on data security, access rights, cloud, or edge processing. Though, training of your sales team will be very important to give appropriate convincing answers.
  • The same is true for your field technicians who need to understand the new technology. Not only to ensure its installation but as well to make use of the machine data during service jobs. 
  • And finally, your after sales team need to learn how to explore the information and react with appropriate offers to the customer (as long as this is not automated yet).    

As your objective was to learn from insides of the machines and to create a bonding to your customer, you will need to put resources to it for monitoring the machine condition and proactively act with offers if required (not waiting the customer to contact you when the problem already occurred). These are important factors to create value for you and your customer, based on Predictive Maintenance. Otherwise, you and your customers won´t experience the benefits of such technology.

Direct your customers to the awesome way.
Stand out with Predictive Maintenance.

The job is not finished with the newspaper laying in front of the door! You only reached your target when your client loves to read your newspaper and is waiting for it. Therefore, you need to learn what he really bothers and what makes him wait for your newspaper under the choice of 1000s newspapers. Data enables you to learn from facts rather than from assumptions, and, if you tap on the opportunity, supports you to realize exceptional customer experience to stand out from the market. Only by knowing and realizing this, you will be able to offer related products or services, which makes your newspaper unique.

At the end of the day, business success starts with customer satisfaction. If you can’t solve the customer’s problem or add value with your machine, any technology, no matter how well chosen, is worthless. On the other hand, if the value proposition is aligned across the organization, the technology will do the rest. 

Interested in Predictive Maintenance?

All about Predictive Maintenance! Let´s stay up-to-date together with our blog which contains our latest knowledge and experience in developing and implementing Predictive Maintenance Solutions.

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