Almost every company today is a big-data company and has plenty of available data but the putting it to use to extract useful information is an ordeal due to lack of robust infrastructure and IT resources needed to derive valuable insights from the huge volume of data. While Data Lakes and strategies around are being put in place it takes lots of resources to derive meaningful decisions in a timely manner!
The answer lies in allowing the data lakes to flourish, yet not to move them around through complex ETL, etc to distill them for decisions. This is where Insights-as-a-Service comes to rescue where a third party service provider will help you in deriving meaningful insights by using uses predictive analytics and business intelligence by hooking on to this data lakes.
Insights-as-a-Service platforms address the need for in-depth analytics and provide solutions to unique data-specific challenges. Also, it allows companies to reduce their costs significantly by removing the need for data scientists and complex infrastructure required to run analytics on premise. With so much benefits, the Insights-as-a-Service market is predicted to grow beyond $3.3 billion by 2021.
Monetizing Data
Insights-as-a-Service not only helps in deriving information from your own data, but it’s also about identifying other data sources which may help in answering specific business questions. As has been the case with many companies, it may look like they have lots of data, with close observation we will find that the information is duplicated, missing critical information or irrelevant to the business question. And this is where data itself is becoming the product.
An Insights-as-a-Service company helps in sourcing relevant data that can help in solving the business problem. For example, a company that has already aggregated data on automotive buying trends can share it with us and we can then collate to get a complete picture.
Insights-as-a-Service gaining traction thanks to the cloud adoption:
Forrester defines Insights-as-a-Service as “an integrated set of data management, analytics, and insight application development and management components, offered as a platform the enterprise does not own or control.”
Till recent times many of the companies were reluctant to share their own datasets and analytics. However, with the wide spread adoption of the cloud computing, companies are now accustomed to the subscription based model and are more than willing to purchasing data, analytics and insights as and when required.
For companies operating on a smaller budget, Insights-as-a-Service cloud platform offers a secure, scalable approach. Insights-as-a-Service solutions are constantly evolving to address company specific data problems, helping them discover what data is relevant, what external data to purchase, and how any of this data can be meaningful.
Components of Insights-as-a-Service solution:
- Vertical Domain Knowledge
For business process automation in the case of certain industries, having domain-specific knowledge is much needed.
- Business Process Discovery
The Insights-as-Service solutions needs a detailed description of the business processes that are automated by SaaS applications. For example, detailed descriptions of the business processes related to planning, corporate financial budgeting and account consolidation processes, customer acquisition and retention.
- Insights Generator
The insights generator includes one or more analytical models such as clustering, prediction, deviation detection and optimization, etc which are incorporated within the platform and the insights are then generated.
- Action Generator
The action generator generates a set of actions that the organization needs to implement in order to achieve its goals. The action steps are derived from the insights generated from the components described earlier.
- Decision Dashboards
Usually, the insights and actions provided are meant for business users who do not usually have any expertise in understanding complex data or codes. So Insights-as-a-Service platforms offer a user interface that makes it easy to understand the insights. For example, the platform can recommend that 25% of the marketing budget be allocated to reduce customer churn and increase customer acquisition.
Conclusion
In today age if DATA is King, then Insights-as-a-Service is the Chief Adviser, helping to take informed business decisions based on data-driven points of knowledge, predictions analytics and insights. In addition if you add the elements of AI, then suddenly you have a winning team! Also Insights-as-a-Service, organizations only need to hire cloud-based services on a subscription model, whenever needed, and acquire insights and actions. There is no need to set up costly infrastructure and hire experts to do the analysis. This way, organizations simply provide the data, and that data is analyzed so that proper actions can be recommended. In the end the elusive enterprise Himalayan Data Mountain is finally negotiated with ease by Insights-as-a-service thus allowing one to focus on the real business!!
Note => Please follow me my post on “Dark Data“ – to understand why Insights-as-a-Service will be key and will play major role in the near future!
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