Data Monetisation: A Complete Guide
With the increasing amount of data that is streamed and processed daily, many companies have realised non-traditional and innovative ways to use this information, such as data monetisation. Data monetisation is the process where company-generated data is used to create a measurable economic benefit. This can include selling data to third parties or using data internally to improve processes or realise new innovation opportunities.
Companies practising data monetisation are realising such benefits like cost reduction, revenue increases, and opportunities for new data-related services. Since the current benefits of data monetisation far outweigh initial financial and time investments, there’s no better time for your business to learn how to develop a competitive advantage through effective data gathering and analysis.
In this article, we will demystify data monetisation, demonstrate how it can dramatically increase business performance, and provide the information you need to know to implement data monetisation strategies.
What is data monetisation?
Data monetisation is the process whereby company-generated data is used to create a measurable economic benefit. Businesses often experience advantages such as increased revenue or reduced expenses as a result of monetizing their data.
Companies can also use their data to construct slightly less tangible benefits, such as new partnerships or improved supplier terms, by sharing their data with third parties in a mutually beneficial arrangement.
In some cases, organisations realise their data has enough value to begin offering data services to a sufficient number of outside companies. Facebook and Google were pioneers of this trend; utilising their free platforms to create enormous data assets to sell across the globe.
Why monetise data?
With only 1 in 12 companies currently monetizing their data to the fullest extent, why should your organisation make the leap today?
- Provides a Competitive Advantage: In mature industries, it’s difficult for businesses to differentiate themselves. Well-executed data monetisation strategies can help to gain an edge on competitors who’ve yet to harness the power of their data effectively.
- Creates New Revenue Streams: Even if you aren’t planning to sell your data to a third party, data monetisation can still generate new streams of revenue. For example, uncovering new customer trends within your data can precipitate the creation of a brand new product to meet those newly-discovered demands.
- Streamlines Operations: For those of you in the manufacturing industry, in-depth analysis of production data can help to streamline output. Companies get to enjoy the positive byproducts of reduced waste and a drop in unnecessary expenditure.
- Create Strategic Partnerships: Data monetisation does not have to be limited to strictly numerical gains. You can offer your data analysis discoveries to interested third parties, such as banks and credit providers, to receive favourable terms in return.
Data monetisation use cases and examples
To give you a better understanding of how data monetisation works in a practical sense, it’s worth giving you a few implementation examples from companies within different industries.
Data monetisation in consumer goods
AB InBev is the world’s largest brewing company. Throughout their growth, they have unsurprisingly acquired many other brands. Today, AB InBev comprises of a portfolio of over 500 global and regional beer brands spread across 100 countries.
Onboarding this number of brands has naturally presented a few challenges. At one point, AB InBev had 27 different Enterprise Resource Planning (ERP) systems and 20 different integration systems to try and tie all of the disparate systems together.
Naturally, AB InBev quickly realised the best way to collate all of the data in one place would be to create a cloud-based data hub. Using a centralised data hub, AB InBev is now able to make more accurate forecasts and reduce product time to market — allowing them to dominate their industry. They now produce the top three selling beers in the US market today, which can be attributed largely to their new data strategy.
Data monetisation in agribusiness
In a high-volume low-margin business, farmers need to have real-time variable information, such as field-level weather and commodity prices, at their fingertips. Digital Transmission Network, or DTN, has been providing those data points to the agricultural industry for over 30 years.
Much like AB InBev, DTN had invested in several different data systems to provide the information that large corporations such as John Deere, Monsanto, and Pioneer utilise daily.
However, DTN struggled with the continued investment it took to manage and maintain an increasing amount of complex applications across several different networks. This strategy limited future growth and product innovation.
As a result, DTN decided to create a cloud-based data tool containing a clear and consistent set of interfaces for each different data field. This eliminated the need to implement millions of costly point-to-point integrations and facilitated a much better user experience.
Today, DTN’s integrated platform is quickly becoming the industry standard for agricultural business data sharing. They monetize their information through a combination of subscription fees and value-added services.
How to prepare for data monetisation in 4 steps
Before you can begin to take advantage of data monetisation and its benefits, it is essential to prepare your organisation.
1. Gain buy-in
The drive for data monetisation must come from the very top of an organisation. Leaders need to grasp that data analytics will not merely serve to save costs; if executed correctly, it can become a source of sizable additional revenue streams.
Once this understanding is achieved, leaders need to stress the importance of this data monetisation process to key internal stakeholders in order to gain buy-in and achieve the best possible results.
2. Assess existing data and determine future collection
An obvious step in preparation for monetizing data is assessing its value. This involves carrying out an audit of the information you collect as an organisation and determining which data provides value and which data requires the investment of extra resources to do so.
It’s also important to remember that you cannot monetize data that does not exist. Key decision makers need to ascertain whether there are any potential opportunities for data points that aren’t currently being measured, either within your organisation or in your specific industry.
3. Decide your audience
Once you have assessed your data for value, it’s time to decide who you are going to “sell” this data to. This audience does not necessarily have to be an outside company. Your audience can actually be critical departments within your own business. For example, data can be used to significantly increase knowledge of consumer behaviour. These data points could be crucial for sales departments, leading to increased conversions and customer retention rates.
If you are presenting the information to outside organisations, however, consider whether the raw data provides sufficient value to them. In some cases, you may have to carry out your in-house analysis to make the data economically beneficial.
4. Establish your objectives
Before you undertake the process of data monetisation, it’s essential to come to an agreement on the overarching objectives.
Whether this is merely an in-house cost reduction exercise, or you are looking to launch a new data-as-a-service arm to your business, you need to make that distinction before starting the process. This is because it is extremely difficult to pivot your overall data objectives after investing in multiple processes dedicated to one specific purpose.
A framework for data monetisation
Once you’ve made the necessary decisions for your data monetisation strategy, you’ll need to establish a process for your company. Below is a broad framework of steps you’ll need to take to take advantage of the benefits data monetisation can provide.
Collect, centralise, and analyse data
It’s essential to develop a data platform from which you can gather all the necessary data in one central location. Once centralised into as few dashboards or interfaces as possible, it becomes much easier to perform analysis and deliver value to key stakeholders.
It’s best if you build or buy a platform where both internal and external parties can log in and find what they need as quickly as possible. This includes granting all parties access to run their own analytics and identify insights to maximise the value of the information gathered.
Consider these two factors before deciding on a platform or solution:
- Building a platform to meet your data monetisation needs may require considerable investment and expertise.
- To keep pace with the increasing size of the datasets and processing capacity, your solution should be cloud-based.
Choose an operating model
There is no such thing as a one-size-fits-all approach when it comes to data monetisation. The highest-performing companies tend to begin with internal data monetisation first, before progressing to selling data to third parties.
However, your data might be more valuable to outside companies than within your own. This distinction will help you choose an operating model that reflects that choice.
Another consideration is whether your organisation will allow other companies to perform analysis within your platform, or if you will instead provide third-party companies access only to view your insights and deductions.
Adhere to governance, compliance and cybersecurity best practises
Perhaps one of the most crucial steps is making sure data adheres to strict governance and compliance guidelines. With data requirements becoming increasingly strict in Europe through its General Data Protection Regulations (GDPR), it is likely that the rest of the world’s governments will follow suit in tightening up data legislation.
Additionally, data integrity is a necessity. Whomever utilises the data must be able to trust its accuracy and consistency. Businesses will be unable to make million-dollar decisions based on analysis of data they have even the slightest reason to doubt.
For very similar reasons, cybersecurity is an essential consideration throughout your data monetisation process. If you cannot demonstrate that sensitive data is adequately protected, then it is unlikely that you’ll have the confidence of a third-party buyer when offering your services. Your information has to be impenetrable to those that try to gain unauthorised access.
The cloud and the future of data monetisation
The shift towards the monetisation of company data has been accelerated by the development of the cloud and cloud-based technology.
Big data cannot be sustainably stored or operated on physical hardware because the costs of maintaining physical networks rapidly becomes prohibitively expensive. On the other hand, cloud-based solutions offer scalable computing power which is able to keep up with the ever-increasing size of data fields.
Additionally, cloud technology allows companies to share real-time data at scale. As already demonstrated, platforms such as DTN’s run millions of data points simultaneously, whilst giving farmers 24/7 access to time-critical information, no matter where they are in the world.
Moving forward, cloud-based technology will further facilitate data monetisation through subscription-based information-sharing platforms. As time goes on, these ventures will make the shift from business-facing to consumer-facing.
Getting started with data monetisation
Data monetisation provides companies with the ability to perform competitive cost reductions, increase revenues, and in some cases, launch their data analysis as a service itself. With the many benefits associated with the use of data monetisation, it’s clear to see why so many businesses are looking to pivot towards utilising their data more effectively.
But setting out on the path to data monetisation is not easy, it requires buy-in from key stakeholders from across the organisation and a serious commitment to building a platform or tool capable of harmonising and analysing the accumulated intelligence. Such tools need to ensure the integrity and quality of the amassed data; otherwise, it could be deemed worthless by both internal and external patrons.
Talend Data Fabric is a single suite of apps that shortens the time to trusted data. Users can collect data across systems; govern it to ensure proper use, transform it into new formats and improve quality, and share it with internal and external stakeholders. Try Talend Data Fabric today to begin monetizing your data.