Massive increases in digitalisation is pushing almost all organisations to become highly data-driven. The ability to collect and analyse data at unprecedented speed and volumes means companies are now viewing data differently. This has given rise to a concept of data monetisation, which refers to the practice of using data for a quantifiable economic benefit.
Data monetisation is certainly not a new concept. However, with the evolution of latest technology, it has taken a different dimension giving new business models for organisations and along with it, the security and privacy concerns for the citizens, governments and private organisations.
For many companies, data is so important that it’s becoming a key asset on the balance sheet. These companies have figured out how to turn their data into money either through external or internal means.
External approaches to data monetisation include selling the data directly to external third parties for marketing purposes. While there are multiple models evolving in terms of direct data monetisation, these can broadly be classified into two categories – first is monetising only data, which involves selling the data in its simplest format to partners or third parties for a one-time or recurring fee; second is monetising data insights, which is more complex in terms of technology investment. Companies have to invest in data analytics capabilities to store, cleanse and analyse the data, and then sell the insights to partners or third parties on a subscription basis or one-off fee.
Direct external data monetisation of this type has led to a huge debate worldwide, after some organisations, such as Facebook and Cambridge Analytica, were accused of unauthorised data selling.
Recently, data privacy acts such as Europe’s revised Payment Services Directive (PSD2), General Data Protection Regulation (GDPR), Australia’s Notifiable Data Breaches (NDB) scheme, and the much anticipated open banking system, are aimed at protecting consumer’s data rights and help provide a regulatory and governance framework for corporates and customers alike.
However, this external monetisation of data is not the only way organisations can turn their data into money. Organisations can use data to identify business process optimisations that drive revenue and reduce expenses. This internal monetisation can be done by almost all organisations.
Investing in analytical capability is no longer optional for data driven organisations, but a mandatory one to survive and grow in the ever-competing market. Companies across all industries, from start-ups to large enterprises, are investing heavily in data analytics to capture, curate and analyse the data to derive meaningful insights.
The benefits of internal data monetisation approach
The most successful companies aren’t looking to monetise their data in just one way, but are leveraging their data insights for benefits in multiple areas. If your business uses data insights to drive decision-making, then you’re already on a pathway to data monetisation.
By investing in basic data analytics, you will be able to identify opportunities for cross-selling and upselling to your customers, potentially increasing your revenue stream substantially. This is a great example of data monetisation in its simplest and most effective form. Beyond that, these insights also provide opportunities to deliver measurable business improvements and cost savings, negotiate favourable terms with business partners, develop new revenue streams based on opportunities uncovered by data insights, or include the data as a value-add component of an existing offering.
Furthermore, you can use data to identify bottlenecks and weak points in your business processes. For example, a manufacturer can install Internet of Things (IoT) sensors around the facility to track the utilisation rates of equipment and monitor productivity and accuracy. The data collected by these sensors can be analysed to illuminate areas for improvement. This can include streamlining processes, automating processes, changing maintenance schedules, and any number of other actions that can have a measurable impact on the bottom line.
A recent survey by McKinsey revealed that data monetisation approaches have significantly or fundamentally changed nearly half of all respondents’ business practices in their sales and marketing functions. More than one-third say the same for research and development (R&D). One of the most important statistics revealed by the McKinsey survey is that 70 per cent of executives reported that data and analytics had caused at least moderate changes in their industries’ competitive landscapes in recent years. This includes disruptive business models that undermine traditional players.*
Statistics like this reinforce the critical importance of data, analytics, and data monetisation. Companies that aren’t yet exploring ways to monetise their data could easily be left behind in a new data-driven landscape.
Getting started with data monetisation
Data monetisation should begin with taking account of your data and identifying what you can use to generate additional revenue or drive cost savings. During this process, you will find that not all data is of equal value. The key is to be aware what data elements you can leverage to derive economic value for your organisation as well as how clean and complete this data is.
Once you have identified the potential value of your data, there are four basic steps to achieving successful data monetisation regardless of the scale at which you intend to monetise your data:
1. Set a strategy:
Before you can effectively monetise your data, it’s important to set a strategy. This starts with deciding whether you’re looking to reduce costs or increase revenue, if this will be targeted towards – internal teams such as sales, marketing, operations; or external customers.
2. Set up a data platform:
You’ll need a technology platform for collecting, storing and analysing data. This can be highly complex depending on how sophisticated you need your platform to be. For example, if you want to share your data with external third parties, you will require a platform capable of doing so securely. The platform may include public or private cloud services, along with data modelling and analytics tools.
3. Prepare the data:
Most of the time, your raw data can’t be used as-is to create value. It requires contextualisation or analysis to derive insights and identify patterns. This is the information that can then be used for business value.
4. Drive the strategy:
Once the tools are in place and the data is ready for use, it’s important to ensure that data analytics efforts are geared towards achieving your organisational strategy. For example, if you’re looking to achieve quick wins in terms of cost reductions, then it doesn’t make sense to interrogate the data for ideas on new products to offer your customers. Instead, you need to keep a laser focus on achieving your stated objectives. This helps ensure your data monetisation project will not only be successful but will also demonstrate its value to stakeholders, setting the scene for continued and expanded data monetisation projects.
Security should be paramount
Given the increasingly tight legislation around data security and governance, any data monetisation strategy must include security from the very beginning. Retrofitting security or governance protocols isn’t ideal, especially since new operating models will see businesses sharing data through integrated systems more readily than in the past. This makes security more complex as well as increasingly important.
Regardless of on-premise computing or new cloud architectures, security must be built in from the start rather than being bolted in at the last phase of system design. The tools and solutions selected to do the data management must support secure cloud services. There are mature API management platforms that aid in security and governance as part of overall data management.
The top priority is to ensure that all data privacy and security legislation is accounted for in any data monetisation strategy. It’s essential to be able to demonstrate strong cybersecurity and privacy capabilities to external regulators, customers, and other stakeholders. Without this, it will be challenging to effectively monetise your data because trust levels will be low.
Customers and other stakeholders won’t engage with your business if they can’t rely on the security of your data. Security should, therefore, be of paramount concern when developing a data monetisation strategy even if it’s just a proof of concept or initial exploration.
Where to turn for help
With so many aspects to consider, data monetisation can be an incredibly complex area for businesses. While most businesses understand the significant potential value of data monetisation, the perceived costs and risks around fully embracing data monetisation can make some organisations reluctant to proceed.
Working with a trusted and experienced partner can dramatically de-risk data monetisation projects and deliver a greater chance of success. Fujitsu’s Global Data Practice can help you integrate data into your business and begin turning it into money sooner, and with less risk. Experience has shown Fujitsu the crucial importance of setting the right data strategy, underpinned by the most appropriate technology platform. By aligning the organisation’s goals with the recommended approach and tools, Fujitsu can help you deliver the required business benefits from data.
It is only appropriate that Fujitsu’s Technology and Service Vision theme for 2019 is ‘Human Centric Innovation – Driving a Trusted Future’ , reflects the growing importance of trust in the digital age, especially in an environment of chaos and complexity. At Fujitsu, trust is a key value that connects our customer’s aspirations to what they can realise in their businesses in the future.
If you’re looking to monetise your organisation’s data, contact us today to find out how Fujitsu can help.
