EXPLORE THE FUTURE

Predictive Analytics - An Engine for Product Development

In the future, collecting data is essential for product development because data creates brand new insights, which pave the way for new business opportunities. It's beneficial for companies to consider how to collect and apply data when developing semi-finished products or components, which as small data pieces are being connected in the final products and services to the customers.

By considering how to apply data in the product development process, you will see new opportunities to improve the product and identify new, related products or services. These initiatives generate profit in one or multiple links in the integrated value chain; from a producer of a component, to the mounter, distributor, retailer, and customer or consumer.

It's beneficial to collaborate with your suppliers and customers, when it comes to data. Data doesn't have boundaries. It might arise as available for one party to collect, then applied by a second party, and at last to be a component in the finished product or service delivered by a third party. No collaboration on how to leverage data will be a loss in potential earnings.

Regardless of whether product development is handled in-house or in collaboration with external partners, it's important to identify where and how each data piece arises in the products and services, you develop, and what and where customers experience it.

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It's the company's Subject Matter Expert and our data scientist that jointly unlock the potential of your data. This also applies to smaller companies when you partner up with our data scientists.

Two Examples of Data Collection in Product Development

Predict the Production of Wind Energy. It's critical for wind energy producers, i.e. owners of wind turbines and wind farms, to be able to predict how much wind energy each wind turbine in a park produces because they are obliged to report expected production to Energinet, which owns and operates the Danish energy infrastructure. Rooftop Analytics has developed algorithms to identify the variables that have the greatest impact on wind energy production, enabling the manufacturer to predict wind energy production from each wind turbine in a wind farm - up to 36 hours ahead of time.

Predict Machine Maintenance Based on Test Results. Over a long period of time, a business has analyzed test samples of oil used in turbines. Based on defined critical metrics, it has been assessed when to change the oil. Based on the test results, Rooftop Analytics can develop the algorithms that identify when the customer should change the oil. In addition, the customer is given suggestions on what maintenance of the equipment should be done. The client benefits from the ability to deliver better customer service by returning oil test faster as well as recommend what maintenance work the customer should initiate, which in the long run can minimize the maintenance costs. In addition, the client achieves operational savings as it employs fewer employees in the analysis department. The client also gets specific data input for the further development of the oil.

The Challenges - Especially for Smaller Companies

Especially for smaller companies, working with data in product development is a challenging task, not least, when it comes to IT investments and resources.

Establishment of IT platform. Although technology is available and has become cheaper, it's still cost-intensive to invest in implementing IT solutions capable of collecting, storing, and analyzing data. Therefore, it's important to make it right – the first time. One approach is to apply interim technical setup while the pilot project is undergoing. When product development seems to be successful, you can invest in IT. Cloud solutions and cloud applications are usually suitable because they are quick to take into use and easy to close down, if the benefits of product development don't materialize. 

Need of a Data Scientist. A major barrier for not thinking data into product development is the lack of data scientists. For smaller companies, there is no business foundation for having a dedicated Data Analytics department or just a single data scientist employed. However, it's not necessary to have in-house expert knowledge of data. You can enter into a collaboration agreement with experts such as Rooftop Analytics. It's the Subject Matter Experts in your company and our data scientist, who in cooperation unlock the potential of the data. You have the unique knowledge of the market, customers, and technical possibilities and limitations, and a data scientist has the right toolkit to work with data.

THE STRENGTH LIES IN THE PERSONAL MEETING

Would you like to obtain a better insight in your data, to verify if your data supports your new business idea, contact Christian Møller Dahl.

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ABOUT ROOFTOP ANALYTICS

When a company identifies new or improved services and products for the market, Rooftop Analytics can analyze whether the available data is relevant, sufficiently supporting the case, and whether the results can be formed solely on the basis of data. With our expertise in statistical methods, models, and algorithms, we develop Predictive Analytics for the benefit of one or more links in the extended value chain.

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See an example of how focus must change over time when data is in play.