It’s no news that we’re in the full throes of a digital age marked by big data and analytics, driven by new technologies that have enabled companies to easily and quickly amass massive datasets from a variety of sources. The real dilemma that this data overload has caused is how to make meaningful sense of all that structured and unstructured data.
This is where insights-as-a-service comes in. As a new trend, people are defining it in many different ways, but in reality, insights as a service is a process through which an external provider makes sense of data for you. In typical “as a service” fashion, it lets you buy only the insights you need, using your own, as well as supplementary data, and analyzing that data to answer specific business questions.
The insights-as-a-service market size is expected to grow from $1.16 billion in 2016 to $3.33 billion by 2021, according to a report from MarketsandMarkets. I believe, however, that it’s only going to get bigger, as data-hungry AI seeps further into virtually every corner of companies both big and small.
If AI is the engine, data is the fuel
AI cannot exist without data—and lots of it, and this is where insights as a service is really reaping the benefits, enabling providers to essentially monetize data that companies, while deluged with their own data, may desperately need to solve the puzzle.
Monetizing data
Insights-as-a-service isn’t only about deriving information from your own data, but also in finding other data sources that help answer your specific business questions. As many companies find, while it may look like you have lots of data, if you look really closely you may find that the information is duplicated, missing critical information or irrelevant to the business question. Just as people may not know what they need until they clean out their closets, companies need to assess their data to determine what additional data they may need.
And this is where data itself is becoming the product. An insights-as-a-service partner can provide you with sourced data that can help support the business case looking to be solved. For example, a company that has already aggregated data on telecommunications buying trends can feed their data into your own telecommunication data to provide a complete picture of customer churn indicators or the likelihood of upselling services.
But what are the types of data that may be required to make business decisions? It includes company data that is stored by the company in CRM systems, databases, web portals, and other locations; or syndicated data, third-party data that can be integrated into company data to create datasets that are information rich.
Insights-as-a-service gaining traction thanks to the cloud
Forrester is clearly seeing the role of insights-as-a-service, dedicating a Wave report to insights platform-as-a-service (IPaaS), which it defines 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.”
While in the past, enterprises may have been reluctant to give up that control of their own datasets and analytics, the pervasiveness of the cloud is changing that, and they are seeing the benefits of the cloud model, which enables them to keep up with innovation, have economies of scale and flexibility. The end result is that companies are now accustomed to the subscription model and more than willing to pay as they go when purchasing data, analytics and insights to drive better business.
What insights-as-a-service can’t do
As industry leaders, like Forrester, acknowledge the marketplace, and as more and more companies turn to services firm to help them accrue more informed data, and subsequently better insights, the market will only continue to grow. Yet, companies need to rein in the enthusiasm when it comes to signing up for insights-as-a-service and seeing it as a way to solve all of their business problems.
The truth of the matter is, while insights-as-a-service is a cost-effective way to leverage data-driven analytics without building up the infrastructure in-house, it’s still a waste of money if you haven’t clearly identified the very specific problem you are trying to solve. For example, instead of looking to find out why profitability was low in a given year, an insurance firm might want to identify the reasons why customer churn is taking place. In this instance, an insights-as-a-aervice provider could hone in on very specific data within your organization, as well as external data about competing providers entering the market, economic conditions, etc.
Additionally, before going the insights as a service route, companies should consider if they already have what they need to make their own informed decisions. before working with a partner, it’s good for companies to identify what they may already have in-house in terms of data. Often, it’s surprising to see how much data you really have across business units. By removing the operational siloes and sharing that information, companies often can identify patterns all on their own.
But for those complex problems that internal data alone can’t address, the good news is that with insights-as-a-service you can invest in the services one problem at a time, so you can decide when you need to bring in the heavy forces.
If today data is king, then insights as a service is fast emerging as the contractual chief adviser, helping to inform business decisions based on data-driven points of knowledge, predictions analytics and insights.