Why CIOs should embrace the potential of data and analytics enablement platforms for a brighter future

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Technology leaders want to harness the power of their data to gain intelligence about what their customers want and how they want it. This is why the overall data and analytics (D&A) market is projected to grow astoundingly and expected to jump to $279.3 billion by 2030. Yet, despite years of investment in varied solutions, many companies still need help to enable their people and partners to connect disparate data sources and effectively collaborate in fully compliant spaces, let alone incorporate AI. That failure can be costly.

In a recent Gartner data and analytics trends report, author Ramke Ramakrishnan notes, “The power of AI and the increasing importance of GenAI are changing the way people work, teams collaborate, and processes operate. Amidst this technological revolution, organizations that fail to make the transition and effectively leverage D&A, in general, and AI, in particular, will not be successful.”

The problem isn’t that organizations lack a wealth of data or advanced analytical tools. What’s missing is the ability to unlock their total, end-to-end values easily. After all, those data sources may be deep, but they’re also usually fragmented across separate data stores and repositories. Analytics applications may individually be state-of-the-art, but they’re commonly disconnected — all of which inhibits ready access, stymies collaboration, limits the customer picture and, worst of all, increases time to insights and marketplace impact.

What’s needed is a unified environment that can enable even multiparty teams to manage the complexity Gartner points to as a significant barrier to success. This is especially important to companies whose bottom lines depend on having robust, real-time pictures of their customers and prospects – any organization dealing with risk assessment, fraud prevention and detection, or marketing. Thankfully, the challenges are being met, and companies are now offering options.

Setting the course: The importance of clear goals when evaluating data and analytics enablement platforms

Improving credit decisioning for financial institutions

Say you’re a bank looking to leverage the tremendous growth in small business through lending. The American Bankers Association (ABA) Journal reported the Dodd-Frank Act now demands small business lending be accompanied by “the type of reporting, data collection, and hygiene currently required for consumer credit.”

That’s a big lift, both in terms of operational expense and regulatory exposure. But the most advanced data and analytics platforms should be able to: a) ingest risk assessment data from a multitude of sources; b) allow analytics teams in and outside an organization to permissibly collaborate on aggregate insights without accessing raw data; and c) provide a robust data governance structure to ensure compliance and auditability.

In short, the correct data and analytics enablement platform can help the bank access new arenas of growth.

Staying ahead of fraudsters — now and in the future

When considering the challenges of fighting fraud in digital payments, we’re no longer talking about just credit card fraud. As the world moves toward a cashless economy that includes electronic payments for most products and services, financial institutions must also deal with new risk exposures presented by mobile wallets, person-to-person (P2P) payment services, and a host of emerging digital payment systems.

A “state-of-the-art” data and analytics enablement platform can vastly improve identity resolution, helping to prevent fraud. Ideally, it will link structured data like traditional offline identities with unstructured data, including behavioral information, device properties, and other factors. This will result in identifying fraudsters more quickly — and at a higher rate — while minimizing false positives.

Empowering marketers to engage consumers at the behavioral level

To build brand loyalty and deepen trust, consumer product companies must engage current and prospective customers in dynamic and constantly adaptive new ways. Unfortunately, traditional data and analytics approaches based on human analysis and transaction-based data are no longer sufficient for that task.

An enablement platform that equips organizations for the future must be able to power consumer intelligence solutions that operate at an interaction scale. Transactions such as a product purchase provide a simplistic “what.” Interactions give the “why.” Pinpointing when a marketing team member emailed a consumer, what they clicked on, from which devices, and in what timeframe and location — and understanding those interactions and how they lead to conversions — creates deep, forward-looking knowledge of customers.

What to look for in data and analytics enablement platforms

Whether choosing a partner for credit, marketing, fraud solutions, or other reasons, it’s essential to compare the underlying platforms they’re built on. Are they equipped with the technology, analytics, and collaboration features needed to take a business into the future? To find out, start by considering the following questions:

1.  Data management

• Does the platform allow rapid, streamlined, and permissible access to all assets and third-party data in a single space?
• Does it enable easy connectivity between a company’s proprietary information and public, offline, online, structured, and unstructured data?
• Will it provide the flexibility needed to work with that variety of data in any required or desired way?
• Are the data governance framework and access controls sufficiently advanced and adaptive to ensure legal and regulatory compliance and auditability?

2.  Actionable analytics

• Does the platform combine human intelligence with AI and machine learning?
• Does it provide a real-time, multilayered, fully contextualized understanding of consumers?
• Can multiparty teams collaborate in clean rooms equipped with privacy-preserving innovations that allow the sharing of aggregated insights without giving access too quickly, and precisely match online, offline, personal, and digital identity fragments to a person or entity to raw data?
• Does the enablement platform solution provider offer analytics and data science consulting services to support a team?

3.  Reliable identity

• Can the platform quickly and precisely match online, offline, personal, and digital identity fragments to a person or entity?
• Can AI and machine learning innovations rapidly adapt to the system— so each use case determines the ultimate decision?
• Can the platform handle noisy digital data, offline indicators, and connectivity elements, while providing extraordinarily nuanced and highly confident decision-making?

4. Robust compliance

• Does the platform leverage standard data governance processes and permission-based controls to help ensure legal and regulatory compliance?
• Is it wholly and easily auditable?
• Can it readily adapt to constantly changing regulations?
• Does it allow you to quickly revisit models as needed?

5.  Self-service

• Can the platform and data be used on-prem and is self-service, avoiding vendor-managed services and costs?
• Can it enable a genuinely end-to-end, DIY data and analytics solution?
• Does it provide access to fresh data to develop more relevant insights?
• Does it lower the cost of acquisition?

6.  Depth of knowledge

• Does the platform create customer intelligence solutions at the interaction level rather than the traditional transactional level?
• Can it take a full range of consumer interactions, codify them into an automated taxonomy, and identify the interactions that lead to desired transactions?
• Does it enable aggregated, contextualized, real-time insights to create behavioral knowledge graphs?
• Can it allow for the quick deployment of diverse and complex AI models?

These are some considerations when conducting due diligence on a data and analytics enablement platform. Hopefully, these best practices will help ensure your company is equipped to effectively manage, govern, analyze, and deliver the data-based insights required for success today and in the future.