Data and analytics are transforming industries, disrupting established business models, and providing unprecedented insight into markets and customers. Savvy organizations are harnessing their data and using analytics to boost revenues and create cost efficiencies. One Indian automotive original equipment manufacturer (OEM), for example, increased its sales conversion by 50 percent by deploying predictive analytics to identify the most promising leads. Such success stories have caught the attention of Asian executives: McKinsey research found that levels of awareness about the value of data and analytics among business leaders in the region increased ninefold from 2011 to 2016.
Despite this rising recognition, many Asian organizations lag behind in actual adoption and risk ceding a competitive advantage to companies that have built advanced analytics capabilities. Our discussions with more than 100 Asian executives reveal that many still struggle to pinpoint the most valuable use cases and fear their organization may lack the strategic path, technology, processes, and talent to implement an analytics program. However, these business leaders can learn from other companies within Asia that have successfully adopted analytics. With this understanding, Asian organizations can confidently take the first steps toward harnessing the full potential of data and analytics.
Increased recognition of advanced analytics’ value in Asia, but adoption trails
Over the past six months, we conducted more than 100 conversations with Asian executives. It’s clear that Asian companies increasingly see the potential value of advanced analytics to their top and bottom lines. A study of the financial statements of more than 2,600 listed companies with revenues above $1 billion in 11 sectors and 39 industries across 14 Asian countries confirms the trend. The presence of analytics keywords (such as big data, machine
learning, and artificial intelligence) in these statements was used as a proxy for awareness of analytics, since greater emphasis in investor communications implies at least a basic level of interest and investment in analytics capabilities. According to this metric, awareness grew from 3 percent of companies in 2011 to 27 percent in 2016, rising to 40 percent when press mentions of companies associated with advanced analytics keywords were included. (For more research findings, see sidebar, “Country and sector comparisons of advanced analytics awareness.”)
But has this increased awareness of advanced analytics translated to greater use of these technologies? Overall, Asian companies (with the exception of China) lag behind their North American counterparts on the level of analytics adoption. Senior executives across Asia cite the following four main barriers to incorporating advanced analytics into their organization’s regular business practices:
Companies resist adopting analytics and executing the necessary operational changes due to a lack of evidence on its business impact.
Organizations with poor data quality struggle to determine whether to fix the issue before scaling or simultaneously as they build out their analytics at scale.
Many companies, having made significant up-front investments in technology without seeing tangible returns, are reticent to commit additional resources.
Due to high employee turnover, companies are left without the deep bench of analytics talent to lead and implement analytics efforts.
These barriers are surmountable, and analytics leaders in Asia and other regions provide valuable lessons as to why it’s worth overcoming these challenges—as well as how to do so.
Advanced analytics adoption: Worth the effort
The use of advanced analytics enables organizations to identify new growth opportunities, become more agile, and understand customer behaviors in more depth. Recent McKinsey research, for example, found companies that use analytics to gain customer insights are more likely to outperform the competition on profits, sales, and return on investment. In Asia, companies have harnessed analytics to support business strategy in four primary ways.
Extract more value from technology
Asian companies are increasingly investing in technologies to become more digital and agile, in part just to keep pace with digitally savvy Asian consumers. The Asia-Pacific region has 2.7 billion unique mobile subscribers, a number that will rise to 3.1 billion by 2020. Asian consumers use their smartphones for a range of commercial activities such as banking, shopping, ordering meals, and hailing rides. B2C players have transitioned from physical to digital applications to meet consumer expectations. Since companies are generating more data across multiple customer touchpoints, they are increasingly employing analytics to track performance, segment customers, and provide the deep insights that help shape strategy.
Increase performance across the value chain
Advanced analytics can also create value by improving decision making and visibility across the entire value chain and ensuring that executives have the insights to manage operations more effectively. In the oil and gas industry, for example, advanced analytics, including applications for capital expenditure reporting, maintenance and inventory, and working capital, accounts for almost 60 percent of all value generated by four categories of technology investments (exhibit). This finding is all the more impressive because the other three types of technology are already in widespread use in the industry.
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Many major Asian economies (Indonesia, Japan, South Korea, and Thailand) are led by large conglomerates: in 2010, conglomerates accounted for 16 percent of the nearly 8,000 Asian companies with more than $1 billion in annual revenues, a share forecast to increase to 37 percent of the 15,000 companies in this segment by 2025. Beyond process digitization and automation, Asian conglomerates have a tremendous opportunity to use analytics to drive deeper insights, collaborate across their holdings and business units, and uncover new growth opportunities. The same potential exists for state-owned enterprises.
Unlock capability at scale
The pace of growth in Asia means that attracting, developing, and retaining top talent is an ever-present challenge. Fortunately, current advanced analytics solutions can uncover insights to help even novice employees improve decision making without requiring years of analytics training.
What it takes to begin a successful analytics transformation
Analytics can have an enormous impact on organizations, but getting started can be a daunting challenge. New investments in technology could be required, new processes must be designed and implemented, and companies must promote analytics-driven decision making, which can be a radically different way of working. To position their companies for success, executives should focus their efforts in four areas.
Experienced leaders start executing data strategies with a focus on high-value use cases and then continually refine based on learnings and results. This approach should be supplemented with a more forward-looking strategy to improve data quality within an organization. Once the initial use cases have been tested and optimized, companies can focus on building out specific models to support the long-term adoption of advanced analytics. Transformations typically start with two to three use cases that can achieve solid results as a way to build momentum and broad support. Over time, leaders develop a use case road map approved by all relevant internal parties to get leadership and top management on board for future planning. Be pragmatic about data and embrace use cases.
The age of analytics: Competing in a data-driven world
Analytics requires the right infrastructure to aggregate and store the necessary data. The most successful companies design their data architecture on a modular technology stack with the flexibility to support the business strategy. This IT infrastructure comprises five building blocks: an underlying data hardware infrastructure, master data management system, streaming data processing, data lake for unstructured data, and an integrated data warehouse both for structured data and reporting. Each of these components can be built modularly, with the suite of components tailored to specific business needs. The layers should be deployed first as a pilot, typically with a six- to nine-month testing window that features a quick, iterative approach. After verifying that technology components clearly meet defined business needs, the full infrastructure can then be rolled out to support the deployment of solutions at scale. Build technology investments to be agile.
Leaders should define a broad range of attractive career paths for their analytics talent, ranging from data science to business-oriented leadership tracks. Although many Asian companies have yet to create these tracks, technology titans Google and Microsoft have long established separate technical and management career tracks that enable talent to develop into executive-level roles. Further, smart leaders combine efforts to develop internal talent with external hires. Focus on developing talent.
Advanced analytics can unlock value only if it is adopted by business users. Executives should define their analytics agenda and hold business-line leaders accountable for both adoption and results. In addition, advanced analytics teams must involve business users as they develop the models. Promote adoption across the organization.
Executives across Asia recognize the value that advanced analytics can unlock, but so far they have struggled to identify and pursue analytics opportunities within their organization. Regardless of industry, we believe it is imperative for companies to take concrete steps to integrate analytics into strategy and operations. The benefits, in the form of greater productivity, visibility, and agility, will be critical to competing in a digital world.