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How Data Can Drive Product Innovation

A common factor among the world’s leading companies is that they use the power of data to enhance their product quality, streamline their processes, operations, and better serve their customers. They also leverage data to develop better products for their customers.
However, product development has always been a risky affair as there’s always the possibility of new product launches failing.

Did you know? Every year 30,000 new products are introduced, and 95 percent fail – a finding by Harvard Business School professor Clayton Christensen!

This is where companies who are serious about getting their products to the masses are focusing on data to drive product innovation success.
From using the right tools to tracing the product’s success to understanding competition, they are leaving no stones unturned for delivering state-of-the-art products using data. The catch is that data sets are large and complex, demanding better analysis and management.
Let’s see how companies are using large volumes of data to enhance their next generation of products and services.

BUSINESS MODEL INNOVATION

Companies that want to accelerate growth need to find ways to shorten their business model cycles. This is possible through cutting-edge innovations in both product and service value creations, which lead to the discovery of new markets and business opportunities.
Business innovation can be either in terms of the development of new revenue streams, identification of distribution channels, or simply new product or service innovation. It is essentially the ways through which a company delivers value to the customers.
Think of firms that have embraced in-app advertising or switched to creating merchandise to woo their customers or doing something else, based on their industry or customers. Both these options have helped various firms achieve their goals of selling products through different methods and earning revenues.
So, where does data fit?
With data analytics, companies can identify the market pulse, know the customer needs and demands, and take quicker decisions. It also helps in accounting, staff recruitment, training, and other processes in between.
To make this possible, firms need to include having a big data strategy and vision in place, which can effectively identify and make the most of new opportunities. At the same time, it is also essential for them to understand and leverage new skills, technology and create an impact with information.

REVENUE OPPORTUNITIES

Data analytics equips companies with the chance to enhance product design, reduce development timelines, costs and contributes to increasing the overall revenue. IDC forecasts that the worldwide revenue from big data and business analytics will reach $187 billion in 2019.

Companies can take the following steps to increase revenue opportunities with data usage in product innovation:

  • Enhance the accuracy and the yield of products
  • Forecast product demand in a better way
  • Aptly streamline the supply planning

Additionally, increasing revenue opportunities is a feat that can be achieved with certain tried-and-tested strategies such as bundling. This is often done by using competitive data from the customers and the data for product demand from the market. The idea is to promote and price the products better to survive the competitive landscape.

Product bundling is one of the best ways to drive product innovation using data. It is best exemplified by eCommerce-giant Amazon, which saw year over year sales increase that exceeded 19% in 2017. The firm offers direct customers and resellers bundling services to maximize their margin on shipped merchandise.

Businesses can apply a similar method to increase their revenue, clean out the inventory and increase the product’ profitability. Data is handy here because the sales records will help reveal the products, which people usually buy as a combo. Similarly, it can help them identify and sort the less popular products with popular products. Last but not the least, data also helps in recommending products.

PRODUCT QUALITY

Product quality is everything.

Behind every superior quality product are exceptional customer service, product reviews, and sales numbers. Sample this, businesses interact with customers on a regular basis via websites, sales, and services. This valuable data helps them understand their customers, their pain points and what makes them tick. Also, data analytics helps bring forth several questions to the forefront such as how to customize or personalize the product to meet their needs.

But most importantly, data can drive better quality by using predictive analytics as this helps reduce the time for quality checks. The tactic was implemented by tech firm Intel, which reported a 25 percent reduction in chip quality processing time with data.

The way forward for firms is to establish strategies that can help gather and analyze data. This can include a database of customer demographics and historical sales data, which can be obtained by using a wide range of data analytics tools and technology.

Businesses can also use the following to enhance product quality:

  • Sales statistics
  • Customer feedback surveys
  • 3rd party customer data
  • Tie up with retailers and manufacturing partners to share sales data
  • Identify bottlenecks with detailed feedbacks, complaints, returns and warranties
  • Track product reviews including those of competitors
  • Opt for social listening to spot the trends

All in all, whatever data is sourced, it should not be used as stand alone. Also, the information should be analyzed properly before it is applied in various aspects of product quality enhancement. This will pave the way for future product innovation.

LIFECYCLE MANAGEMENT

Data also makes it possible for firms to manage their end-to-end product lifecycle. It equips them with the ability to zero in on the product improvements, the incremental changes and significant changes made to the products.
Applying data analytics to product lifecycle needs a focused approach. Companies need to use the right data using internal coordination. The teams working on the product can coordinate and work together with the information available and derive inferences that make sense. This can help several manufacturing firms to change the way they approach product design, reduce iterations and also, enhance the products’ usefulness in the long run.
Data empowers companies to change their product game, help them manage the lifecycles enhance the quality, come up with a new business model and revenue opportunities to take product innovation to the next level. If your business still hasn’t made the shift yet, it is high time you go for the transformation and start leveraging your data.