Analytics as a service: Why more enterprises should consider outsourcing

With an increasing number of enterprise systems, growing teams, a rising proliferation of the web and multiple digital initiatives, companies of all sizes are creating loads of data every day. This data contains excellent business insights and immense opportunities, but it has become impossible for companies to derive actionable insights from this data consistently due to its sheer volume.

According to Verified Market Research, the analytics-as-a-service (AaaS) market is expected to grow to $101.29 billion by 2026. Organizations that have not started on their analytics journey or are spending scarce data engineer resources to resolve issues with analytics implementations are not identifying actionable data insights. Through AaaS, managed services providers (MSPs) can help organizations get started on their analytics journey immediately without extravagant capital investment.

MSPs can take ownership of the company’s immediate data analytics needs, resolve ongoing challenges and integrate new data sources to manage dashboard visualizations, reporting and predictive modeling — enabling companies to make data-driven decisions every day.

AaaS could come bundled with multiple business-intelligence-related services. Primarily, the service includes (1) services for data warehouses; (2) services for visualizations and reports; and (3) services for predictive analytics, artificial intelligence (AI) and machine learning (ML). When a company partners with an MSP for analytics as a service, organizations are able to tap into business intelligence easily, instantly and at a lower cost of ownership than doing it in-house. This empowers the enterprise to focus on delivering better customer experiences, be unencumbered with decision-making and build data-driven strategies.

In today’s world, where customers value experiences over transactions, AaaS helps businesses dig deeper into their psyche and tap insights to build long-term winning strategies. It also enables enterprises to forecast and predict business trends by looking at their data and allows employees at every level to make informed decisions.

Win over customers strategically

Analytics is integral to refining the customer experience today. Return on experience (RoX) is becoming an important metric to measure customer experience, but most organizations do not have the bandwidth to filter customer data and develop a thorough understanding of customer experiences at each touchpoint or further personalize them.

Let’s, for example, assume that a retailer wants to figure out how its customers’ attitude toward in-store shopping has changed during the pandemic. With AaaS, they can quickly generate a report for their customer’s buying patterns and also leverage data for forecasting inventory.

The best part is, companies don’t need to shoulder the administrative burden of setting these reports up or maintaining them — their MSP takes care of the setup, back-end work, maintenance and resource management. Freeing up resources also enables an investment path for strategies such as using AI-powered chatbots and virtual assistants to reduce the burden on customer service and accelerate response times while boosting customer satisfaction.

According to Gartner, by 2022, 90% of companies will consider information as an asset. This is because a company’s ability to take forward-looking decisions will be enhanced by the information that enterprise data captures and its ability to analyze it.

By harnessing the full potential of services like data mining, predictive analytics and AI to unearth trends and insights from existing data sets, AaaS can empower organizations to capture and exploit short-term and long-term business trends, including but not limited to sales forecasting and demand forecasting. The best part is that companies will not need to make any changes to their existing infrastructure to be able to do all of this.

Even companies with less developed IT capabilities can leverage this service for complex predictive and prescriptive analytics.

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Decentralize decision-making and cut costs

Faster decision-making is the cornerstone of fundamental business transformation. However, it’s critical to create an agile and flat enterprise where employees at all levels have access to the correct data. With AaaS, MSPs can provide enterprises with insights on demand for everyone in the organization.

To provide actionable intelligence end-to-end, companies don’t need to invest extravagantly to procure additional hardware or expand or train their teams. The MSP provides the infrastructure setup and skilled resources, so organizations can skip the lead time needed to create a decentralized setup and provide their workforce with data intelligence.

Cost-effectiveness is an added advantage. As with other hosted solutions, AaaS is more cost-effective than managing hardware, software and resources to deliver efficient analytics. It allows companies to have recurring and expected billing based on the subscribed services.

While predictable cost is a bonus, the two most significant benefits are: (1) The ability to jump-start the data insights journey without getting into procurement and other preparatory tasks; and (2) get analytics experts on board immediately without going through the full hiring cycle.

Getting started with AaaS

Choosing an MSP with a strong data insights team and experience in providing AaaS is the first step. Next comes helping the MSP perform a business intelligence maturity assessment of the current process, tools and IT infrastructure to understand how AaaS can bring short-term and long-term value. The third and final step is to work with the MSPs to set realistic objectives about what the company wants to achieve in a defined time frame.