How Software Vendors Can Jump-Start Integrating Analytics Into Their Applications

Chandana Gopal

There is no question that the digital economy requires that enterprises treat data as the lifeblood of their organization. As digital transformation expands around the world, enterprises have new technology options, marked by the emergence of intelligent technologies such as machine learning, artificial intelligence, blockchain, and the Internet of Things.

Enterprises also face more complex business ecosystems and recognize that they must become data-driven to succeed. In fact, IDC has created a digital transformation (DX) platform that demonstrates the importance of putting data, information, and technologies at the core of the new digital ecosystem. Enterprises must invest in intelligent technology, people, and processes that leverage data to drive revenue, accelerate innovation, and maximize their odds of succeeding in this complex and evolving digital environment.

The importance of data and analytics in an intelligent enterprise cannot be over-emphasized. Without analytics, enterprises cannot gain insight and make intelligent decisions. IDC predicts that by 2022, over 60% of global GDP will be digitized, with growth in every industry driven by digitally enhanced offerings. According to research done by IDC’s Global DataSphere, humans generated 33ZB of data in 2018 and are projected to generate 103ZB per year by 2023. The problem is that the vast majority of data generated today is lost. In fact, only about 2.5% of all data is analyzed. To optimize the chance of business success, enterprises are now looking for ways to generate insights from this huge quantity of data.

The new digital ecosystem

To accelerate their transition to a data-driven organization, business owners and stakeholders are looking outside their enterprises towards independent software vendors (ISVs) that can help them create value and drive rapid innovation based on data. ISVs are responding to this demand by creating new intelligent solutions and services. Because analytics and insight are core to an intelligent enterprise, there is a growing connected ecosystem of ISVs, analytics software providers, data providers, and professional services providers coalescing to create immense value for their customers.

Forward-thinking ISVs are partnering with technology platform providers to give them differentiating capabilities as part of their software offerings, creating new business models that can be monetized into new revenue streams.

The cloud advantage

While analytics tools have been around for several years, cloud analytics is relatively young. There are several benefits to using a cloud analytics platform, such as scalability, modern architecture, ease of deployment, and global availability. The benefits of partnering with an analytics platform provider that offers a cloud delivery model go beyond licensing software. For ISVs that have invested in building an infrastructure with a provider, often the primary consideration is how best the analytics solution fits with the underlying infrastructure.

ISVs must figure out how to deliver on this. That means building data-driven apps with the next-generation analytics power capable of learning, predicting, and visualizing business outcomes and processes. Doing this rapidly with low risk and cost means accelerating the move to the cloud and partnering with an analytics platform provider that has the tools to match your requirements.

ISVs have found that embedding cloud analytics, or extending and modernizing their apps with a cloud analytics platform, enables them to create new opportunities to grow their business. ISVs should take the following factors into consideration when choosing an analytics platform provider:

Partner with a platform provider or build organically?

While there may be some benefits to building analytics offerings from scratch, such as lower cost if using open source technologies, ISVs often find that building an analytics solution has hidden costs. Typically, it takes longer to implement and is more difficult to scale and support.

What are the benefits of partnering with an analytics platform provider?

  • ISVs that have already made infrastructure investments related to a certain platform provider often benefit by deploying cloud analytics from the same vendor because of pre-built integrations.
  • Platform providers offer technical support, training, and implementation resources. They continue to invest in incorporating the latest innovations into their products and cloud deployments, making it easy to access those innovations.

What should the purchasing criteria be?

  • Does the software meet most of the requirements for my use case? Is my use case unique in any requirements (e.g., ultra-high transactional volume, near real-time integration with other systems, IoT)?
  • Can I find training resources to help with implementation and ongoing support?
  • Do I have any technology dependencies on other infrastructure elements?
  • Can the platform provider scale with my growth (12-month, 3-year, 5-year growth plans)?
  • What is the total cost of ownership of the analytics solution?

Next steps

  • Tap into the discussion: Hear from SAP, IDC, and SAP partner Kaiserwetter as they discuss the research findings and explore the critical factors and trends related to integrating analytics into commercial software offerings. Watch the replay here.
  • For the full story on developing intelligent applications with integrated analytics, download the IDC white paper, “Critical Factors and Trends in Analytics for Independent Software Vendors,” sponsored by SAP. Download here.

Chandana Gopal

About Chandana Gopal

Chandana Gopal is Research Director for IDC Business Analytics Solutions market research and advisory practice. Ms. Gopal's core research coverage includes demand and supply trends in business intelligence advanced and predictive analytics, and enterprise performance management markets. Based on her background in integration and analytics, Ms. Gopal's research includes a particular emphasis on how analytics is being embedded into software applications, how artificial intelligence is being embedded into business analytics software, and how end users requirements are driving technology design.