Simply put, productising data is targeting the impact on the end user down the stream
Given the extraordinary rise in user-generated data and improved internet bandwidths, startups consider it an essential asset and are reworking their data landscapes
Data productisation reduces time to insight, improves decision-making, and generates new revenue streams
There has been plenty of discussion about the massive amount of data generated in real-time and the opportunities to monetise it.
While startups are flocking to build data-driven consumer products, most of them succumb to insufficient management models at the back end. This happens because data management strategies are not aligned with the consumer experience. Exactly what, data products are trying to resolve?
What Does Productising Data Mean?
Data products are reusable data assets that are implemented across the landscape to facilitate a targeted end goal. A data product platform collects data sets from various sources, organises them, and makes them available to anyone with authorisation.
Simply put, productising data is targeting the impact on the end user down the stream.
All those services largely dependent on data quality get better when we treat data as a product. Therefore, you need to organise it and make it easier for your consumers to find, trust and use it.
Data products address the complexity arising out of data sets sitting in silos due to the following reasons:
- Fragmented data sets across a multitude of disconnected source systems
- Confined in vendor applications that normally don’t have a rich API set
- Confined in legacy systems with little or no exposure to the underlying data model layer
- Structured variably in different formats and technologies
- Not in compliance with regulations thereby risking the confidentiality of user and organisational information
As a result, 80% of data in traditional models is left abandoned, inaccessible and under-utilised. This data is a great opportunity missed for enhancing customer experiences.
What Happens When Enterprises Productise Data?
Given the extraordinary rise in user-generated data and improved internet bandwidths, startups consider it an essential asset and are reworking their data landscapes.
Their zest to become a data-driven entity is evident from Mckinsey’s popular findings that suggest data-driven companies are 23 times more likely to acquire customers and 19 times more likely to be profitable.
Data products outperform projects by delivering better ROI, backing multiple outcomes while focusing on emerging use cases.
Creates Better Consumer Experience
As mentioned above, data products facilitate a certain end goal such as a greater consumer experience. Some of the benefits include:
- No need to create a new product every time. This ability to reuse data products ensures quicker time-to-insight
- Assures end-to-end data integrity with trusted and fresh data sets every time
- Data augmented with real-time insights assures contextual accuracy
- Enables timely and optimised decision-making due to in-the-moment response times for various use cases
- Qualitative data sets that are compliant with all governance policies
- Data is easily accessible and discoverable
Enables Faster & Scalable Data Management
Data productisation reduces time to insight, improves decision-making, and generates new revenue streams. Data products are packaged assets that include meta information to enable real-time use cases, perform analytics, or achieve simple end goals by utilising data.
Let’s understand this with an example of K2view. They implement an innovative architecture to collect business entities from a multitude of source systems and integrate them into an exclusive micro-database for each. These high-performing databases are accessible to authorised consumers and receive continuous fresh data feeds.
Their data product platform manages billions of such micro-databases. With such an approach, data products perform concurrent management of workloads in large enterprises. Not to miss, the data product management system can be delivered through the Integration-platform-as-a-service (iPaaS) in the cloud, totally on-premise or for hybrid system landscapes.
Such an approach accelerates the implementation in weeks, supports scalability and achieves faster time-to-insight. All of it, at zero downtime. This enables them to deliver value incrementally in agile circumstances. Not to miss, the data product architecture is future-proof which makes it scalable and adaptable to changes.
Reduces Operational And Security Costs
One of the greatest outcomes of using data as a product is cost-effectiveness. Normally, the human resources in an enterprise spend significant time gathering, cleansing and organising data sets. Sometimes, critical functions like financial analysis are done manually, making them labour-intensive and exhaustive.
Data products automate and fasten the process thereby producing more accurate and timely insights for the systems. This makes the product adaptable and suitable for a wide range of sectors.
Cyber-attacks emerge as leading cost overheads. The severity of enterprise data succumbing to cyber-attacks needs no introduction. Most of the time, it is the lack of a strong data management layer that makes theft easier. As per Statista, 21.4 Mn users were affected due to data breaches in 2021. And this is a crucial driver for enterprises to embrace data assets as a product and thus build better protocols.
Enables Personalised Consumer Experience
The thumb rule of digital selling is — the more and sooner you know about the interests and preferences of your customers; the more likely you are to close a sale. In pursuing the same, you need more qualitative data assets to feed your systems.
You can achieve total personalisation and meet your customers’ expectations by putting data products at the heart of your predictive strategy. It matters because 63% of surveyed consumers expect personalised communication in product suggestions, order confirmations and others.
For example, segmenting marketing campaigns for consumers who have similar interests gets faster and smarter with data products. Other examples include auto-completion of payments and auto-adjustment of product catalogues as per the device used by the consumer.
Get Ready! Web 3.0 At The Doorstep
As it has been said a million times, data is the new gold and may drive the global economy in the future. Businesses, therefore, are working towards utilising the powerful asset in an agile environment. While Web 3.0 is on the doorstep, scoping large volumes of data produced in real-time is a priority.
In this article, we discussed the meaning, importance and scope of data products in building a better startup. What motivation do you have to embrace data productisation? Do share with me.