Point of View

Why a Smart Analytics Strategy Is Critical to Driving Your Digital OneOffice Transformation

November 21, 2018

Analytics has gone past the point of being a “nice to have” capability and has become a “must have” for any business. It is critical for business leaders to think about getting value from data more deliberately and effectively than in the past. The impact of data and analytics initiatives has been limited thus far—usually limited to ad-hoc analyses and siloed data exploration.


Managing data has now become a strategic imperative for business growth: 79% of enterprises are planning or piloting smart analytics towards realizing speed to market, improved customer experience, and operating cost reduction (Exhibit 1). Business leaders have the opportunity to incorporate smart analytics to influence broad-based business outcomes, going beyond siloed world views. This POV explores embedding data and smart analytics across the C-Suite as the foundation of the digital OneOffice.



Business leaders must prepare for the smart analytics “arms race”


Data and analytics are taking center stage as key contributors to business performance (see Exhibit 1). In fact, data and analytics are finding new stakeholders and executive support as automation, AI, and machine learning become commonplace terms in boardroom discussions. Our research identified analytics and machine learning as the biggest value creation levers for broad-based business outcomes. These include accelerating speed to market, improving customer experience, and driving down operating costs.


Exhibit 1: Smart analytics is the top value creation lever for achieving critical business outcomes 



Source: HFS Digital Transformation Study, 2018; Total n = 352


HFS defines smart analytics as focused on improving enterprise decision making by using cutting-edge computing techniques across a wide range of analytics activities, with the ability to sense, comprehend, adapt, and recommend. Smart analytics uses unstructured and structured data and includes techniques such as machine learning and predictive analytics. Smart analytics augments human decision making, where humans make final decisions after receiving actionable recommendations from machines that learn and improve over time.


As their roles get more complex, the C-suite needs data more than ever


Enterprises that ignore the advancements of smart analytics do so at their peril. They risk losing market share to competitors that are driving more informed decision making to create highly personalized products and services, effective customer engagement, and intelligent supply chain networks. As an example, Sears recently declared bankruptcy following years of sharply declining sales. What was once the largest retail store in the world failed to respond to its shifting business climate, unlike competitors such as Macy’s and JCPenney. Through the years, Sears chose to focus on cost-cutting instead of understanding and responding to changing customer preferences and experiences in-store and online.


Clearly, the explosion of digital data has thrown open the applicability of smart analytics across the C-suite (Exhibit 2). Enterprises’ fundamental business models are rapidly changing, with consumerism, digital disruption, and, most importantly, a data explosion creating both new problems and opportunities to compete and win.


Exhibit 2: The C-suite’s need for smart analytics



For a recent example, the business drivers for data are what CVS’s recent bid for Aetna seem to be about. Amazon, the world’s third-largest retailer, recently announced that it was going to start selling prescription drugs, putting legacy retailers like CVS on the back foot. How do you compete with the “Amazonification effect,” where you’re required to have an incredible data and analytics backbone, personalized and intuitive customer sales interfaces, and an unbeatable logistics infrastructure? While CVS and Aetna represent a reaction to the dynamic healthcare environment, this merger also seems to be about data as CVS will gain new services and data informatics from Aetna.


How should organizations think about embedding smart analytics into operations?


The enterprise-wide shift to smart analytics and a “data culture” will see three fundamental changes in how companies view their use of data.


  • Business-led. The stakeholders and executive sponsors for data and analytics initiatives will expand from IT into more business-centric roles under the C-suite.
  • Cross-functionally collaborative. Functions like finance, marketing, and IT will need to collaborate in new ways, breaking down their silos to better share data and get unique insights and visibility into how their work impacts partners and customers.
  • Smart about using unstructured data. The concept of “relevant data” will expand for most operational processes as business leaders realize the applicability of unstructured data. Unstructured data makes up most of the data available in an organization (see Exhibit 3). Harnessing this data will allow enterprises to digitize operations and build in ways for employees to make more informed decisions.


Exhibit 3: Business leaders will need to get smart about using unstructured data



Source: HFS Research, 2018, “Intelligent Operations Study” conducted in association with Accenture, Sample: 460 Global 2000 Enterprise Buyers


These indicators are part of how HFS envisions the future of business operations as the OneOffice organization. The OneOffice conceptual framework enables enterprises to collapse the silos of front-, middle-, and back-office processes and reorient them to deliver better experiences and outcomes for all stakeholders, leading with the end customer (read more here). Smart analytics plays a critical role in this. The OneOffice evolution uses smart analytics and digital technology to drive predictive insight for proactive action and better outcomes–higher quality, speed, and profitability.


Exhibit 4: Smart analytics at the center of the OneOffice organization



Source: HFS Research 2018


The smart orchestration of data and insights—smart analytics—is the foundational pillar that supports all the fundamental principles of OneOffice initiatives:


  • Fundamental 1: Fostering digital customer, partner, and employee engagement. The use of ethnographic research and behavioral sciences to augment traditional customer data will drive a more nuanced understanding of customer, employee, and partner experiences and the motivators and influencers to improve them.
  • Fundamental 2: Embedding design thinking techniques to achieve continuous digital outcomes. Using design thinking principles can greatly improve the end user experience on the collection, analysis, and interpretation of data and insights (read more here). Design thinking is one of the best ways to influence cultural change, keeping the end user’s needs in mind, whether they are in reporting, HR, or IT.
  • Fundamental 3: Building a scalable digital underbelly that automates and digitizes. Moving to cloud-based data infrastructure, creating data lakes, and overall data consolidation and modernization efforts are critical to developing a digital underbelly that can support smart analytics.
  • Fundamental 4: Achieving an intelligent digital support function without hierarchies and silos. Embedding operational insights across horizontal business and IT functions, creating self-serve analytics and reporting interfaces, and providing better access and real-time availability of data are all goals that will create intelligent digital support functions.
  • Fundamental 5: Establishing intelligent, cognitive processes that promote predictive decision-making. The focused use of machine learning and deep learning and other advanced analytics technologies to provide predictive and prescriptive guidance will help enterprises to better anticipate and respond to market changes.


Bottom line: Your company’s future is dependent on how quickly the C-suite can drive a smart analytics discipline across operations. Use the Digital OneOffice fundamentals to prioritize your organization’s focus areas around data.


Ultimately, the need for smart analytics is simple. We are increasingly operating in business environments built around “infonomics”—the idea that businesses should consider data to be a strategic asset, with opportunities for monetization across business functions. Information value is going to skyrocket in the hyper-connected economy, and smart analytics holds the key to unlocking it.

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