The Five Rules of Data Monetization PDF

Summary

This document outlines five rules for successful data monetization. It emphasizes understanding data's role in business, organizing data effectively, aligning monetization with business strategy, and recognizing the diverse opportunities data presents. This document highlights the growing importance of data as a valuable asset for businesses.

Full Transcript

Ondřej Kulhánek | 1 May 2019 https://home.kpmg/xx/en/home/insights/2019/04/the-five-rules-of-data-monetization.html The five rules of data monetization How do we value our data? That's the question so many in business are asking at a time when the volume of data available to companies is growing exp...

Ondřej Kulhánek | 1 May 2019 https://home.kpmg/xx/en/home/insights/2019/04/the-five-rules-of-data-monetization.html The five rules of data monetization How do we value our data? That's the question so many in business are asking at a time when the volume of data available to companies is growing exponentially. What companies are realizing is there is no finite answer. Unlike tangible assets, the value of data can grow the more ways it is utilized and the more insights that are drawn from it. No wonder then that data monetization – literally defined as the process of increasing the economic value of data – is becoming such an important and growing area for all businesses. Through data monetization your business can start treating data as an asset and gain the benefits from maximizing its value. The potential for data to deliver value for many parts of the business is enormous. How then can your business succeed at data monetization? From our* experience these are the five rules you need to follow. 1. Understand the role and value of data in your business Good data management is about making sure you have the proper data to support your business and improve performance. Smart data utilization also helps in managing risk and provides assurance that the business is compliant with laws and regulations. But it can only serve this purpose effectively if you know where your data resides, how relevant it is and how valuable it could be. Often companies fail to accurately value their data because it is not strictly accounted for as an asset even though it has real worth in external markets. 2. Get your data house in order Too many companies lack metadata – i.e. data about data – such as the data quality, where it's stored and what it means. In fact, many companies are more likely to have a more detailed inventory of their office furniture than their own data. Before thinking about monetizing data, companies need to discover what kind of data they hold about their partners, customers, products, assets or transactions and what publicly available data can be called on to increase the value of their proprietary data. They must also work out whether that data is of value internally to cut costs, streamline operations or improve sales processes, or as an external revenue stream such as customer intelligence as a service, or both. 3. Embed data monetization into business strategy and get the right structures in place Too often corporate strategy is not supported by related data management initiatives and vice versa. Executives should evaluate their key business goals and strategic initiatives through the lens of how data can support them. Consider the energy sector where a company that applies service-oriented asset management can gain a lot of insight into individual materials and parts or the equipment. This information can be used to barter better terms and conditions with the material and parts vendor. Once you understand the quality of data and have tied it to business strategy then you can put the right structures in place to monetize it. Often this involves assembling a multi-disciplinary, cross-functional team – including information product leads, data management experts and executives from sales, marketing and operations – to create a platform for business innovation powered by the data. Together they can determine ownership structures for different data sets while making sure that sense of ownership doesn't result in data bottlenecks or siloes. 4. Be open to new opportunities The potential for data to deliver value for many parts of the business is enormous. Sometimes, though, it's hard for companies to imagine quite what the opportunities could be because they are so used to pursuing growth through established strategies and revenue streams. That's why all companies should be open to learning from other businesses and partnering in ways that make sense from a data point of view. Take the example of one telecom company in the Czech Republic. It was able to package the geographical data it had about mobile phone users to help a national park better understand where visitors were coming from, how long they stayed in the park, and, by analyzing traffic flow data, was able to model which special events prompted increased visit footfall. Armed with this information, the park optimized its services and marketing and saw a 10 percent visitor increase. 5. Communicate data's value internally and externally to foster growth Monetizing data is still a relatively new experience for many organizations, and even when successful initiatives are in place they aren't always known to the business as a whole. As data becomes more and more important, companies will need both to communicate and educate internal and external stakeholders so they fully grasp the value data can deliver. One approach for internal awareness building is to brainstorm with those professionals in charge of data or with business function leads to show them how data can improve their business processes. What types of data could really help change their work, offer a competitive advantage or open up new revenue streams? Then there are the success stories of companies monetizing their data – these tend to win over even the most skeptical of executives. Gathering direct customer input is also important. What benefit do they see in the data you can give them access to? However, external data monetization initiatives do need to pay heed to issues concerning legal, privacy, intellectual property, logistical and technological delivery. Ultimately, the sooner companies educate themselves and settle on a strategy to monetize their data the better. With the amount of data increasing at an exponential rate, those companies that understand its potential and can monetize it shold enjoy a real advantage over competitors that still struggle to understand its true business potential.

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