Today, most businesses still have difficulty evaluating the costs and benefits of data in a concrete manner: bit and byte monetisation efforts do not present a tangible opportunity for businesses as evidenced during the recent international Outsell DataMoney Conference.
It had already been highlighted in last year’s Outsell’s report that data monetisation would be the prime growth opportunity for companies in 2017. In fact, during the latest industry conference, Anthea Stratigos, co-founder and CEO of Outsell Inc, estimated the value of data in the various sectors, identifying for 2016 alone an information market value of 1.6 trillion dollars. The largest market share being represented by consumer media worth 627 billion dollars and the marketing and communications sector worth 463 billion dollars. The credit, financial and tax sector reached 157 billion dollars, while education, training and human capital management was worth 149 billion dollars.
Data has become a “booster”, with the Chief Data Officer and the ‘Emerging’ Chief Analytics Officer as the money-makers. Know-how in developing applications and analytical skills that leverage data constitute a competitive advantage for companies and an important indicator for overall business performance. Combining big data with artificial intelligence, the internet of things, automatic learning and robotics, entire sectors such as food and agriculture are reinventing themselves.
How do we capitalise on data? The Agile process
The process of evaluating the costs and benefits for data development begins with two fundamental questions: which is the supply offer that should be built and maintained over time? And what are the prices accepted by customers?
Companies that want to market their data or create effective data-driven solutions can follow an Agile process cycle with 4 phases:
- Conceptualisation and definition of the product offer, namely the identification, segmentation and sizing of the reference market, identification of end-user needs, assessment of the competition, concept verification and definition of top-level architecture.
- Once the offer has been defined and the target market determined, the business process moves to feasibility assessment and prototyping. At this point companies should identify and select content architecture and technology; negotiate whether to build or buy the data and technologies to be used in the supply offer; evaluate the products that will be used to obtain the market supply; define user interactions; develop testing and launch plans and review the prototype with users.
- Tactical distribution and marketing, where the product is actually produced, the price is finalised, sales channels are established and sales performance is evaluated with respect to competitors.
- Measuring performance, namely analysing web statistics, profitability assessment, measurement of ROI and customer loyalty, executing the benchmark and a decision to either review or halt supply.
The value chain: the pyramid model
According to the Outsell model on DataMoney, the value chain is a pyramid structure where the lower levels of the pyramid offer the most applicable solution to a wide range of potential clients.
The so-called commodity data is placed below the pyramid and constitutes the building block for other data services. Data-only companies are usually located at the lower part of the pyramid because they are easier to replicate with respect to the tools and analyses that are instead positioned at the top of the pyramid. The next level of the pyramid is value-added content, or so-called “intelligent data”, which for example is categorised or indexed. The subsequent level consists of access and detection tools such as search, mapping, and viewing. These tools serve as access points that facilitate discovery, show relationships and create meaning.
What is needed to monetise data?
An important consideration for companies trying to monetise their data is the frequency with which said data is updated. It is very important to consider the need for speed, especially in certain sectors such as those related to financial services.
The determining factor for a company is choosing whether or not to create its own business data platform, since consideration must be given to potential licensing mechanism limitations in the use of third-party platforms that may lead to delays and difficulties.