How can I transform my data to profit?

People say: “Data is the new gold!”, but how can you convert this into turnover as a machine builder? This is a question we often get from our customers. ROI or return on investment is the big driver behind this question.

Monetizing the data is actually creating a positive impact on business results through the use of data. This can be done directly and indirectly.

The direct way: business models behind data

Despite the rapid progress and high-tech character, the machine building industry is rather traditional in terms of business models, mainly because customers do not want it.

Customers do not allow machine manufacturers to access their data, they are afraid to share data. Nevertheless, there are opportunities and we are convinced that data can create enough value to market it. A few options at a glance:

Predictive maintenance or a service contract

The most obvious and easiest to market is a service contract. By means of the data in combination with analysis, you can better estimate when the machines need maintenance. This saves valuable time or unnecessary maintenance costs for the end customer. By intensively monitoring the machines you have a good picture of the health status and you can avoid downtime by planning maintenance automatically! This service offers enormous added value for both the machine builder and the machine user, in terms of quality, reliability, efficient use of time, customer satisfaction, etc.

An additional advantage is that you can upsell by selling spare parts or offering other extra services.

Develop digital products/services

Selling digital products or services on top of the current machine is a way to convert data into profit. Some options we see there:

• The optimization package
  It can be deduced from the data that is captured whether a machine is being used optimally or not. An optimization package will advise the end customer on how to improve operational efficiency with some adjustments in user behaviour.
• Part monitoring
  A derivative of predictive maintenance can simply be the monitoring of critical parts and timely warning customers to avoid a production stop.
• Automatic supply of consumables
  You can also look beyond your own machine, but focus on the end result and the resources you need for this. Keep control over the entire process and even manage the supply of consumables. For example: As a bottling machine, give the order to deliver a new batch of empty bottles or even go a step further and make a link with the ERP package to automatically order the empty bottles from the supplier. Perhaps it is even an option to sell the consumables yourself and this can also generate additional income.

Pay-per-use model

This is a model also known as Machine-as-a-Service. Instead of selling the machine, you can enter into lease contracts with your customer. If you really want to go to pay-per-use, you can only charge the customer for the use of the machine, in the form of time or finished products. By means of dashboarding and reporting, you can keep the customer informed of the costs and make an estimate of your cash flow.

IoT subscriptions

Provide your customers with insights into real-time and historical machine data that offers clear added value. Make sure this is presented in a very accessible and user-friendly way. The right data, for the right users, everywhere, at any time and on any device.

The indirect way: improvements through data analytics.

It is easier to calculate direct impact on the operating result by linking business models. Too often indirect revenues are not included in the ROI calculation. But what are some indirect ways to influence the operating result through data.

Cost savings

By creating insights into the performance of your machine, you know exactly where optimizations are possible. Identify possible pain points and by means of a structural solution you save time, money and increase customer satisfaction. A small adjustment can have a big impact on your bottom line result.

Market a better product or service

We have already mentioned it before, insight into data ensures that you can continuously improve your product or services. This can be done through product optimisations, but another example is that you gain insight into user behaviour. How are the machines used and how can we improve the user experience? An answer to this question is more valuable than developing unnecessary features.

Develop new features or enter new markets

Developing features is a major investment, while there is no return yet. By means of data, user insight in combination with market knowledge, you are perfectly able to develop and sell new features.

An alternative is that the insights also allow you to address a new type of customers or markets to which you previously had no reach.

What now? How do I get started?

What are the steps I should take? There is no golden formula, but the following guideline can guide you to a good solution.

Step 1: Determine your goals and analyze customer needs

Step 2: Investigate different models and make a selection

Step 3: Start small-scale with a proof-of-concept together with a customer

Step 4: Scale-up and realize your strategy

One final tip: Enter into discussion internally and externally, with colleagues, users and providers. Our experts are ready to provide you with the necessary guidance.