While turning up the spotlight on the fourth industrial revolution (Industry 4.0), Malaysian agencies have also included Big Data Analytics among certain transformational shifts in the way businesses operate.
In an exclusive Computerworld Malaysia interview in Kuala Lumpur with Shilpa Aggarwal, who is associate partner at McKinsey & Company, discusses how advanced analytics, artificial intelligence can improve decision making for companies.
This interview takes place in the context of McKinsey's recent acquisition of talent and assets from VLT Labs, a Malaysian digital business builder and product development studio based in Kuala Lumpur (KL).
As VLT Labs has more than four years of digital product engineering and design experience, specialising in helping corporations to conceptualize, design and build digital products. VLT Labs will join the existing team within McKinsey Digital Labs, which includes developers, designers, IT architects, agile coaches, and data engineering experts.
Nimal Manuel, Managing Partner, Malaysia, McKinsey & Company commented: "We are committed to growing a digital studio in Malaysia to serve our clients across the region. We are proud to have found exceptional talent in home-grown VLT Labs to help us achieve our mission. We look forward to integrating the team of designers, developers and product managers into McKinsey, taking them to serve our clients globally."
Photo: Shilpa Aggarwal, Associate Partner, McKinsey & Company
To start with - could you please briefly talk about your role and what excites you about the current landscape?
I am an Associate Partner within McKinsey & Company and I co-lead the Advanced Analytics practice for SEA. I am passionate about bringing this new science of management to clients in different industries as well as analytics maturity. A lot of this stems from my own client work. I serve leading technology and telecom companies on improving performance through data enabled transformation.
While analytics has been around for long (companies have been collecting and analysing data for many years), the landscape has changed dramatically in the last few years - driven by 3 key factors.
The first thing that has changed - very simply, there's a lot more data. About 90 percent of the world's data existing today didn't exist two years ago. Secondly, we have computing power, with cloud and connectivity, which is at greatly reduced cost than ever before - so we can compute more. And finally, by leveraging machine-learning techniques, we can analyse so much more.
Do you think there are differences on how emerging technologies are playing out in Asia's business sectors?
Artificial intelligence (AI) is still in its early stages in Southeast Asia: the use of machine learning-an AI application in which machines are given access to data to learn from-is just beginning to have an impact on the region.
If Southeast Asia wants to catch up to the United States and China, the two major hubs of AI development, it needs to coordinate efforts to put fundamental building blocks in place.
All member states of the Association of Southeast Asian Nations (ASEAN) are engaging in some level of AI research and we see early deployment across companies in Malaysia. Example; Hong Leong Bank in Malaysia is using a cloud-based AI system to gauge customer's emotions by the way they speak on telephone. The use of virtual assistants is more widespread but very few firms in SEA have scaled AI use cases like credit scoring and dynamic pricing. So early stages for AI in SEA.
So what are the expected real business returns from AI and other emerging technologies?
Companies that combine strong digital capability, robust AI adoption and a proactive AI strategy see outsized financial performance. In fact, we categorized the ways in which AI can create value into four areas:
- Enabling companies to better project and forecast to anticipate demand, optimize R&D, and improve sourcing
- Increasing companies' ability to produce goods and services at lower cost and higher quality -
- Helping promote offerings at the right price, with the right message, and to the right target customers;
- Provide rich, personal, and convenient user experiences.
These four areas of value creation are based on specific use cases that are being explored or have been deployed in businesses today.
Example; A European power distribution company was able to reduce its cash costs by 30 percent over five years by changing its maintenance patterns based on remote analysis of 20 variables to determine the overall health of power transformers. And the impact will vary by industry and by scale of implementation.
Moving on to insights from data, what challenges are you seeing when working with companies?
While details of implementation for each company will be unique, our research and experience suggests that excellence in four areas is crucial to gaining value from big data analytics as a complement to strategy:
- A solid anchor to business value
- A pragmatic approach to IT
- Attracting scarce talent
- Providing insights to the front line.
Decision making is one of the keys in making real changes: Exactly how can advanced analytics and artificial intelligence enhance the decision making process?
After decades of false starts, artificial intelligence is on the verge of a breakthrough, with the latest progress propelled by machine learning/AI. Looking at case studies of digital natives and responses from our survey, we find early evidence that AI implemented at scale delivers attractive returns.
For example, AI allows businesses to provide better forecasts for their supply chain and design better offerings. AI-based approaches to demand forecasting are expected to reduce forecasting errors by 30 to 50 percent from conventional approaches. Lost sales due to product unavailability can be reduced by up to 65 percent.
The German online retailer Otto uses an AI application that is 90 percent accurate in forecasting what the company will sell over the next 30 days.
How is McKinsey helping to drive big data and advanced analytics?
We meet our clients anywhere they are in their journey to become data-driven, providing everything from specific expertise on discrete issues to holistic transformations spanning strategy design, build, implementation, capability building, and ongoing support.
Our iterative, end-to-end approach starts with the identification of opportunities and culminates in broad adoption of new ways of working, all while ensuring that the underpinning technology and organizational model are optimized for each client's specific needs.
Many organisations fail in the execution of analytics programs because they don't build the skills and culture needed to embed new analytics capabilities into their business processes. To ensure that our clients are successful-and will continue to thrive long after our work together is complete-we go beyond the delivery of new models to help them build the capabilities they need to sustain their analytics advantage over the long term.
How we work
- Identify sources of new business value: Every analytics project starts with identifying specific opportunities for analytics-driven revenue growth and performance improvements. We then develop a road map based on a broad range of potential solutions.
- Expand the data ecosystem: We work with clients to build extensive data ecosystems. We assess the sources of data that are available both inside and outside a client's organization, and we enable the creation of new data using affordable technologies such as the Internet of Things (IoT) and smart sensors.
- Build models for trusted insight: Working within integrated client-service teams, our data scientists select the best models and approaches (ranging from basic forecasting to advanced machine learning) and then customize and improve them for the specific client situation, applying deep functional and industry knowledge.
- Integrate user: friendly tools We ensure that the tools we develop allow users at all levels to intuitively connect with data to make new discoveries. Starting with the delivery of mobile visualization techniques and robust self-service environments, we help clients create cultures of curiosity that foster innovation.
- Manage adoption: We help clients understand how these new tools work so they can use them consistently. We collaborate up front, follow up with communication on model performance, and heavily invest in training people across the organisation. By working to ensure that they have the right data-governance strategies in place, we help foster trust in the quality of the data and the resulting insights.
- Create technologies and infrastructure: Our team of software engineers, data engineers, scientists, visualization experts, and consultants can work either within a client's existing environment or on Nerve, our cloud-based platform. Nerve delivers capabilities and solutions in a highly secure and encrypted environment affordably and effectively
- Optimise organisation and governance: We help clients build the IT architecture, data governance, and organizational capabilities to capture the potential of big data and advanced analytics, and we work to ensure that analytics is adopted seamlessly across the overall organisation.
Could you talk about McKinsey's partnerships in the wider artificial intelligence, data and computing ecosystem?
We continue to invest in selected partnerships and acquisitions. We recently created a "New Ventures" structure that leads market scouting and partners' selection/ negotiation. Our Analytics division is one of the fastest growing of our Firm, comprising more than 1000 dedicated professionals and an increasing number of partnerships; for journey analytics, for artificial intelligence, and on digital capability building. We have also acquired several leading providers of analytics capabilities including QuantumBlack, Risk Dynamics, PriceMetrix, and AOE.
What's your final takeaway for business and IT leaders in this region?
There are vast opportunities in AI, but the key to capturing it isn't having the best algorithms (though that certainly helps) -- it's understanding how analytics can drive competitive advantage, identifying where it can have the most impact, and building capabilities across the organization to make better decisions with data.
To see some other Malaysia news about Industry 4.0, visit:
- MIMOS kick-starts Malaysia's Internet of Things blueprint
- Feeding the 4th Industrial Revolution in Malaysia, MIMOS sees two major talent moves
- Securing the Internet of 'Nano-Things,' an exclusive with NanoMalaysia CEO Dr Rezal Khairi Ahmad
- What's really in store for Malaysia's IT industry in 2017?
- This is how Gartner sees artificial intelligence playing in Malaysia's digital disruption: interview