Building the Case for Real-time Active Intelligence

Business thrives on intelligence. When it comes to executive decision-making, data-driven intelligence matters, but many rely on experience and best practices at the operational level.

So, when COVID-19 threw a curveball at the business normal, it also threw a wrench into established practices. Companies had to become agile and responsive while staying resilient to market shocks. These factors saw many companies switch to digital.

But switching to digital is not as simple as flipping a switch. As companies look for near real-time insights for faster decision-making across their organizations, your data availability and the speed at which you create actionable insights become crucial.

It was the subject of a recent virtual roundtable titled "Making the Digital Switch: Practical Steps to Real-time, Active Intelligence in Action." Organized by CDOTrends in partnership with Qlik, participants discussed the rising value of data, the challenges today's data workers face, and how companies can get ready for a real-time data-driven world.

A Focus on Creating Data Pipelines

Wararak Arnamwat, account director and country manager for Thailand at Qlik, who opened the discussion with a presentation, noted that companies realize they need a culture of innovation to remain agile and resilient. Data can help to shape such a culture.

Tools are constantly improving.  Piya Paitoonrajitpipit, the solution architect for Thailand & ASEAN at Qlik, demonstrated how easy for non-data science employees to analyze data intuitively.

However, the participants noted that manual and inefficient data processes get in the way. According to a parallel survey conducted with the attending participants, the top culprit hobbling data-driven efforts was manual workflows and processes. Other issues that participants highlighted include poor integration of data sources, data governance concerns over PDPA, and tightly controlled information.

Paitoonrajitpipit noted that automating data workflows should be a key focus of data-driven projects, and it should embody data governance right at the beginning. He highlighted Qlik's Active Intelligence approach that looks to turn raw data into informed actions quickly.

Part of Qlik's promises lies in providing a robust end-to-end data and analytics platform. Paitoonrajitpipit shared that companies cloud use Qlik Data Integration, Qlik Catalog, and Qlik Data Analytics to derive actionable insights quickly. For more advanced analytics, companies can then send the data to the data science teams.

This approach allows employees to make decisions quickly at both strategic decision-making and operational levels. It also offloads the data science team, allowing them to focus on more advanced analytics activities.

Another challenge is the time-to-value of data. Here, companies see some data holding more value at specific periods and becoming less relevant at other times. In the participant survey, participants highlighted delayed insights and the organization not being ready to make decisions in real-time as important reasons why turning data into actionable insights was a challenge.

Strong Demand for Real-Time Data

Closing this time gap is one of the fundamental promises of Qlik's Active Intelligence approach, said Arnamwat. It uses a framework based on data integration, data analytics, and data literacy as a service to get timely insights.

Arnamwat highlighted three points when describing Active Intelligence:

• Active Intelligence is based on continuous intelligence. It is a design pattern in which real-time analytics are integrated into business operations, processing current and historical data to prescribe actions in response to business moments and other events.
• From real-time to up-to-date information. The ability to process data in real-time is a key differentiator from traditional BI. While historical data remains vital for many use cases, Active Intelligence can deliver the most up-to-date, accurate information.  The combined use of data at rest and data in motion drives better decisions and outcomes.
• Designed to trigger immediate actions. At the heart of Active Intelligence are augmented analytics woven directly into operational processes that can take or trigger actions when specific conditions are met. It ensures that the right actions are taken at the right moment as events unfold.

However, real-time means different things to various functions and companies. And in some cases, companies may want to focus on getting their data and analytics platform right first, said Sanpetch Tangsawapark, vice president for compliance in ASEAN at Nissan Motors Thailand Co., Ltd. 

"It really depends on the industry. If you're much closer to the consumer, it's very relevant," he explained.

Tangsawapark also noted that one immediate challenge was legacy data. The way the data was captured and stored may not be ready for real-time data analytics. For his part, he focused on data cleansing to get the data ready first.

Despite this, most participants surveyed said that they've heard about Active Intelligence and understood the concept. One participant also said they practiced it.

Finding the analytics sweet spot

Arnamwat explained that Qlik's human-centered design approach puts the analyst's needs at the center, allowing them to get to actionable insights faster.

Most analytics projects look at it from technology and data availability perspectives. Arnamwat observed that business viability and people desirability are often ignored, leading to poor adoption or analytics projects that do not deliver the data consumers want.

Qlik's approach considers analytics from all four angles: data, technology, people, and business. Where all areas intersect is what Arnamwat explains as the sweet spot for innovation.

Puntrika Baingern, director, senior executive vice president and chief financial officer for the accounting and finance group at Muangthai Insurance PCL, this sweet spot mattered when COVID-19 hit. It helped insurance companies like hers to sell policies without having the ability to do face-to-face transactions and only having online channels to sell.

Another success story shared at the discussion was that of Bank BTPN. The Indonesia-headquartered bank wanted to speed up data-based transactions and improve data availability. The goals were to personalize customer service and reduce the strain on its current core systems.

Arnamwat explained that with Qlik's help, the bank prevented interruptions to the core banking systems and enabled near real-time data access for multiple units. More importantly, it created a 360-degree view of their customers, which many see as the "golden record."

Getting closer to the customer

For Muangthai Insurance's Baingern and Nissan Motors' Tangsawapark, creating the golden record that remains current and updated is a major goal of the existing data projects. Having a holistic view of their customers will improve business revenues and allow companies to stay agile to new customer needs and opportunities.

With today's uncertainty, having a holistic customer view is not just a competitive differentiator; it's a business imperative. It is why in the survey, participants cited improving decision making with better business transparency and having a 360-degree of customers as the top two motivations for pursuing data-driven projects in the last 12 months. 

Winston Thomas is the editor-in-chief of CDOTrends, HR&DigitalTrends, and DataOpsTrends. He is always curious about all things digital, including new digital business models, the widening impact of AI/ML, unproven singularity theories, proven data science success stories, lurking cybersecurity dangers, and reimagining the digital experience. You can reach him at [email protected].

The views expressed by the panel discussion participants are personal. It does not necessarily represent their companies, organizations and institutions unless explicity stated. Image credit: iStockphoto/metamorworks