The use of data analytics to guide business decision-making is nothing new. Organizations have been adopting it to measure sales and improve customer satisfaction, among others. If so, then why all the recent hype? Is there a difference today?
Yes there is, according to a recent report published jointly by Ernst and Young (EY) and Forbes Insights. In an era of widespread business disruption, the stakes are higher than ever. To maximize the value of data analytics, executives are embedding it into all parts of their enterprises, beyond traditional pockets such as marketing and sales departments.
The report, High Stakes, High Rewards, revealed that only 7% of organizations have a well-established analytics strategy that is central to the overall business plan. Compare that with 38% of companies that have analytics strategies for specific lines of business, but not fully aligned across the enterprise; while 10% stated that they currently lack an analytics vision or strategy. Yet, of that 7% among organizations, 66% said they achieved revenue growth of 15% or more in 2016, while 63% reported a jump of at least 15% in their operating margins. Moreover, 60% of these companies said they also enhanced their risk profiles.
The report — which is based on a survey of 1,518 global executives belonging to organizations that had at least $500 million in annual revenue — found that given the returns, more than half of the respondents plan to invest at least $10 million in data analytics over the next two years.
Unsurprisingly, increased sales or revenue and improved customer satisfaction ranked highest overall in terms of the reasons for using data analytics. However, upon closer examination, organizations have varying motives, depending on their proficiency in applying data analytics. Those that have well-established strategies are interested in how they can use data to strengthen themselves for the future. In particular, they want to transform business models, develop new products, respond more quickly to market changes, and develop closer relationships with partners and vendors.
By contrast, companies that have less-developed strategies hope to accelerate decision-making, deploy personnel more effectively, and improve current products or services. In terms of the type of advanced analytical approaches, market-leading organizations use predictive modeling (67%), artificial intelligence (53%), and robotic process automation (43%).
The report also revealed that selected industries and business departments are better at understanding the importance of using data analytics more effectively and that they are finding ways to better capitalize on their rich data reserves. Companies in the manufacturing and financial services sectors demonstrated the most progress in developing a sophisticated data analytics strategy. Other sectors that posted solid progress were government, health care, and technology. What this means is that — while every industry is being disrupted by new digital technology, market insurgents, and shifting customer demands — these five sectors are facing particularly intense competitive pressures. As a result, they turn to data analytics to differentiate themselves from competitors and evolve their products and services.
The need to enhance data analytics proficiency can also be felt across departmental functions. For human resources, the intense global competition for highly skilled talent is a top priority. Similarly, in the age of e-commerce and online reviews, maintaining a high level of customer outreach is the key to brand loyalty. Sales and marketing, two areas that have been long-time consumers of data, are under more pressure than ever to devise new ways to generate revenue and use targeted campaigns to connect with customers.
In the Philippines, many business owners are cognizant of the urgent need to incorporate a data analytics strategy into their overall business plan. The 2016 Microsoft Asia Digital Transformation Study — which surveyed 1,494 business leaders from Asia, including 111 from the Philippines — found that 86% of the Philippine respondents agreed that every organization should become a digital business to drive growth and that fresh data insights can generate new revenue streams. However, the journey to becoming a digital business remains a work in progress for most organizations, with only 32% having a full digital transformation strategy. Forty-three percent are in progress with specific digital transformation initiatives for selected parts of their business, while a quarter of the Filipino respondents have very limited or no strategy in place.
Respondents cited lack of leadership to formulate and execute a digital transformation plan, cyber threats and security concerns, lack of competent employees, and insufficient government support as barriers to digital transformation. These reasons resonate with the global findings of the EY-Forbes Insights study.
The EY-Forbes survey, however, revealed that the problems change as enterprises become more mature in their application of data analytics. The report said that organizations that have underdeveloped systems often struggle with issues relating to budgets, lack of full commitment by senior executives, and inadequate leadership. Companies that have started to implement an analytics strategy and view it as a key component of the business plan may have at least partially addressed those early problems, but other issues, such as a lack of collaboration among different stakeholders, become more prominent.
Organizations that have a fully developed analytics strategy are not immune to challenges either. In particular, the study found that they often encountered a lack of collaboration and alignment within the management committee, as well as insufficient senior-level commitment and support for data-driven cultures. When devising strategies, stakeholders should also find ways to overcome the lingering effects of intuition-based cultures where decisions are made on the basis of “gut feel” instead of relying on data.
To address these challenges, the report put forward several recommendations. First, stakeholders should clearly define their desired objectives and ensure that proposed initiatives are closely aligned to these goals. Second, businesses should prioritize recruiting, developing and retaining individuals who can serve as analytics “leaders” in various parts of the organization. Further, there is need to determine the competencies and roles that are needed across business teams to ensure that the right mix to drive initiatives actually exists. Third, data in itself can be considered a business asset and the insights derived from analytics can be used in assisting decision-makers of what new products, services, and capabilities to create. Fourth, the report encouraged closer collaboration among stakeholders from all relevant departments and the removal of organizational and policy barriers that prevent the successful implementation of data analytics strategy. Last, despite the increasing application of artificial intelligence and other forms of automation in business, human judgment will remain a vital element when making strategic decisions. Executives should continue to consider the change management effects of applying advanced analytics imperatives across the organization.
In essence, factors like technological innovation and new customer demands are rapidly transforming the way we do business. Organizations that are not adapting fast enough are at an increased risk of lagging both current competitors and emerging players that have placed data analytics at the core of their strategy. To stay competitive, it is vital for companies to find a way to analyze and give meaning to the massive amount of data flowing through their systems.
This article is for general information only and is not a substitute for professional advice where the facts and circumstances warrant. The views and opinion expressed above are those of the authors and do not necessarily represent the views of SGV & Co.
Wilson P. Tan is the Vice Chairman and Deputy Managing Partner of SGV & Co.
