The Race To Understand Customers in Real-Time: An Indonesian Adventure

Image credit: iStockphoto/SergeyNivens

Lukas Djuanda was feeling the weight of his company’s data-driven decisions.

The chief information officer for JAPFA Group, a Pan-Asian industrial agri-food company public-listed in Singapore and Indonesia, Djuanda wanted to quickly unlock the business potential within his company’s data. So, the Group deployed ERP and business intelligence programs to streamline its operations, improve management and help make informed decisions.

This was where they hit a performance wall. Spending hours collating and adding Excel data and creating time-consuming reports as demand for data soared slowed down decision-making. Djuanda knew it was time for real-time analytics.

“It was increasingly apparent to us that our then-BI platform and Excel spreadsheets were no longer tenable. This was when we embarked on a journey to look for a new BI platform,” he says.

The real-time conundrum

Indonesia is only at the start of its real-time analytics journey. Many like Djuanda see the need for it. But as companies embark on this journey, they face several challenges.

In the Gartner report “5 Essential Practices for Real-Time Analytics,” the authors and analysts W. Roy Schulte and Pieter den Hamer observed that people “mean different things when they say ‘real-time’.” This ambiguity creates confusion when creating goals for real-time

data analytics projects.

The analysts argued that real-time analytics should not be limited to event stream processing platforms. “Almost any analytics, BI or AI product can be used for near-real-time analytics as long as it uses current input data,” they wrote.

Companies need to understand when they want real-time, said the Gartner analysts. “Determine the ‘right time’ for analytics by working with business people to understand the business conditions and requirements. Real-time is not always the right time,” they added.

The Gartner analysts pointed out that companies need to build guardrails into automated and human decisions, design systems to present essential information at the right time, and improve organization-wide situational awareness by sharing real-time data across the conglomerate — what the industry calls data democratization.

Increasing data privacy and security laws in Indonesia are also adding to business complexity and making real-time analytics complex. “The advice for Indonesian companies is to make use of analytics, BI, and AI and don’t be too distressed about privacy and security. But, of course, you should be putting governance at every step of the process, from when a piece of data is created to when it is used to take action, and around analytics,” says Andreas Nataniel, the country sales lead for Indonesia at Qlik.

Indonesia’s conundrum: too much data

The good and bad news is that Indonesian companies are sitting on lots of data — making Indonesian companies data-rich and information poor.

“That is the spot-on problem. Indonesia, with the fourth-biggest population in the world, is a data-rich nation. Indonesian companies are sitting on a gold mine. One way or another, every individual is generating data, and this is the native data market for Indonesian companies,” says Nataniel.

Djuanda understood this “gold mine” very early, a reason for his company’s initial foray into BI. But it was not enough. “Our goal was grand but simple. We wanted a BI platform that would allow us to enable a data-literate organization: adjusting course, direction, and business decisions that are based on unquestionable facts and figures,” he adds.

For conglomerates and multi-corporations in Indonesia, business diversity is a source of strength. Yet, this same advantage creates challenges when managing data stored across different business units and subsidiaries.

“That was when we came across Qlik. What impressed us the most was its built-in script-based ETL, its Associative Engine, Power of Gray, and in-memory processing capability; all without costing us an arm and a leg,” Djuanda explains.

Understanding the Active Intelligence Promise

Qlik’s Nataniel believes that Indonesian companies face three distinct challenges when it comes to real-time analytics.

The first is the mindset. “The understanding of how to use real-time information to help their interactions with the surroundings (such as customers) is the key to adapting to business situations quickly,” he says.

Data silos, which are common, varied, and numerous in Indonesian companies, create standardization headaches. Each data silo owner is also located in different departments with different sets of processes and tools, making data management complex.

“And without standardization, all of these processes in data pipelines are becoming tangled up, spaghetti-like,” adds Nataniel.

The first step to addressing the above challenges is to “free” the data for further consolidation and analytical processes. It is also the first step of Qlik’s Active Intelligence approach.

“ Qlik provides an end-to-end, real-time data integration and analytics cloud platform to close the gaps between data, insights, and action. Unlike other vendors offering traditional BI tools, we transform data into Active Intelligence, enabling businesses to tap into the pulse of that data to take informed action at the moment. This leads to better decisions, improved revenue and profitability, and optimized customer relationships,” explains Nataniel.

For JAPFA’s Djuanda, Active Intelligence offered a different approach to traditional BI. In the past, the company entered data “one by one” so that they could detect any anomalies in their chicken farms in near-real-time and prevent any significant concerns.

“The reality was that more time was spent on processing and converting raw data into meaningful reports and charts than analyzing and gaining insights from the data,” he shares.

Qlik reversed the situation with Active Intelligence. Nationwide data from across the thousands of hen houses that JAPFA operates now automatically flow — processed and transformed — into meaningful visualization insights on a regular and timely basis.

“Whenever Qlik detects a potential anomaly, it immediately sends an alert to proper authorities. Insights are also highlighted in different colors to make them visible: green for when everything is good, yellow and red for when something is identified according to the severity of the anomaly. Details behind those indicators are also just a click away as Qlik allows us to drill down to the level of details we require,” adds Djuanda.

Taking the next step

Pooling the different data sets and deriving real-time actionable insights is not a means to an end; it is the first step in the Active Intelligence journey.

The next step includes increasing data literacy. Indonesian companies will need more people to understand, interpret and be curious about the data-driven insights.

“Active Intelligence builds on what is commonly referred to as ‘continuous intelligence.’ This means that the system leverages real-time analytics, which is embedded directly into business operations — providing continuous access to the most up-to-date, accurate information right where users need it. The capabilities of embedding directly to everyday business operations are hand-in-hand with data literacy level in the organization,” says Qlik’s Nataniel.

For JAPFA, they are also looking at predictive analytics to become more proactive, not just react faster.

“I think the next step is to progress to predictive and script-based analytics. What if we could create accurate predictions given historical data and parameters from our ocean of data? What if our data could give us steps towards the desired outcome or identify preventative measures? That is where I see the data revolution taking us. Given the advancement in the areas of machine learning and AI, I have high hopes this is going to happen sooner rather than later,” says Djuanda.

This article is part of a DataScience&AI Trends eGuide. You can download the entire copy here.


Winston Thomas is the editor-in-chief of CDOTrends, DigitalWorkforceTrends, 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].

Image credit: iStockphoto/SergeyNivens