How Insights-as-a-Service Solutions Use Big Data for Future Planning


Insights as a Service applied to big data can be a powerful tool to help organizations plan ahead.

Big data offers companies unprecedented opportunities in the form of insights. Needless to say, insights can be translated into revenue if properly harnessed. However, for various reasons, it is not always easy to unearth insights from the enormous volumes of data generated from different sources. The task gets more difficult with the volume of data growing every day. It has been estimated that in 2015 alone, 2.7 thousand exabytes of data were generated.

Insights as a Service are a set of applications specialized to generate actionable insights from big data. These applications have been garnering a lot of attention recently. Companies need such services to analyze data and find relevant and actionable insights. Therefore, Insights as a Service has appeared as a boon.

What Is Insights as a Service?

Insights as a Service is a software service that specifically delivers quality, actionable insights. Typically, such services are hosted in the cloud. Of course, these services cannot operate on their own and need to be helped by data and analytics from other services. So, other SaaS solutions generate analytics and Insights-as-a-Service solutions create insights from these analytics. The insights not only provide important information but also suggested actions to achieve a business goal. This is explained with the help of the example below:

A mobile service provider plans to launch a 4G mobile Internet service and wants to promote the service across its existing customer base. An Insights-as-a-Service solution can help the company achieve its goal in the following steps:

  1. An analytics service first identifies customers who are already using mobile Internet on their smartphones or other mobile devices.
  2. The analytics service then gives ratings to customers based on their purchase history, subscriber plans, data usage, payment history and other data.
  3. The Insights-as-a-Service solution takes over from here. It takes the analytics as a base and identifies the customers that the mobile service provider should focus on.
  4. The Insights as a Service identifies the actions the mobile service provider should take and the budget that should be allocated.

So, the Insights as a Service does a lot for the companies: it tells the companies what to do and how much budget to allocate. (To learn more on SaaS, see How APM, SaaS and Analytics Are Streamlining Application Management.)

Companies Providing Insights-as-a-Service Solutions

There are several companies that provide such services. A few of the companies that we are going to discuss are Acteea, 9Lenses, JBara, Host Analytics and 8thBridge.


How Does Insights as a Service Work?

As mentioned earlier, these solutions cannot work independently, and depend on the following things:

  • Data generated by a number of sources such as proprietary corporate data, SaaS applications, open source and syndicated data. For example, Host Analytics, which offers an analytics application for corporate performance management, integrates the customer’s budget data with data from CRM and ERP SaaS applications and open-source industry-specific financial data to generate insights. In the same way, 8thBridge combines its customer’s data with open-source data about Facebook, YouTube, Tumblr, Flickr and Twitter usage as well as Klout score to create the Social Commerce IQ index.
  • Deep domain expertise or knowledge of industry-specific business processes. For example, the solution offered by Acteea leverages a lot of the keyword bidding process used by ecommerce retailers for search advertising.
  • The Insights-as-a-Service solutions incorporate a lot of best practices from the industry. For example, the solution offered by JBara incorporates a lot of best practices for improving customer retention and profitability.
  • Strong analytic practices on predictive modeling and optimization.
  • Data on benchmarking practices followed by companies to compare their performance with that of peers and competitors. For example, the solution offered by 9Lenses allows a company to benchmark its performance on various dimensions with its competitors.

The above section describes the dependencies of Insights-as-Service solutions. A typical Insights-as-a-Service solution comprises five components which are described below. (For more on the use of analytics, see The 4 Key Benefits of Business Analytics.)

Insights Generator

The insights generator incorporates one or more analytical models such as clustering, prediction, deviation detection and optimization, depending on the requirements. These models are incorporated within the application under a different framework. The insights are then generated and imported into the application. For example, the application by JBara develops its own deviation-detection analytics to provide insights on customer satisfaction.

Business Process Description

The Insights-as-Service solutions need a detailed description of the business processes that are automated by SaaS applications. For example, the analytic applications by Host Analytics incorporate descriptions of the business processes related to planning, corporate financial budgeting and account consolidation processes. Similarly, the application by JBara incorporates descriptions of the business processes related to customer acquisition and retention.

Vertical Domain Knowledge

For business process automation in the case of certain industries, domain-specific knowledge is needed. An example is Odyssey Solutions, which caters to the chemical industry. This also applies in the case of the customer acquisition process in B2B commerce.

Action Generator

The action generator generates a set of actions that the company needs to take in order to achieve its specific goals. The action steps are derived from the insights generated from the components described earlier. For example, the application by JBara offers actions that can potentially reduce customer acquisition costs. The actions are derived from its deviation-detection analytics.

User Interface

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, many applications offer a user interface that makes it easy to understand the insights. Companies like 9Lenses, JBara and Host Analytics already provide interfaces and before that, they determined which content should be presented textually, and which graphically. Other than presenting information, these applications also display suggested actions. For example, the application can recommend that 10% of the marketing budget be allocated to reduce customer churn and increase customer acquisition.

Case Study

The case study of Nottingham University Hospitals NHS Trust (NUH) establishes how insights can make a difference in the context of a business. The Nottingham University Hospitals NHS Trust used insights to predict demand for its services and identify trends. For this, NUH used parameters such as age, demographics, health parameters and so on. The insights services were provided by a third-party provider, Nottingham Insight. According to the NUH deputy director of strategy, Keith Reynolds,

“Nottingham Insight helped us to analyze health trends in the Nottingham area so we could prepare the strategic direction for our services over the next five years. As the information on Nottingham Insight is shared with our other key stakeholders, we avoided any potential problems arising from incompatible data and findings.”

The key thing in this case study was the actions suggested by Insights as a Service and how NUH could benefit by following the suggested actions.


With Insights-as-a-Service solutions, rather than needing an expert on staff, organizations only need to hire cloud-based services on a subscription basis, 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.


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Kaushik Pal
Technology writer

Kaushik is a technical architect and software consultant with over 23 years of experience in software analysis, development, architecture, design, testing and training. He has an interest in new technologies and areas of innovation. He focuses on web architecture, web technologies, Java/J2EE, open source software, WebRTC, big data and semantic technologies. He has demonstrated expertise in requirements analysis, architectural design and implementation, technical use cases and software development. His experience has covered various industries such as insurance, banking, airlines, shipping, document management and product development, etc. He has worked on a wide range of technologies ranging from large scale (IBM…