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July 30, 2019
Navigating a successful data-driven transformation
By: Alison Kennedy, Tony Gomes and Oliver Bittner

A guide for going from basics to mastery

In this age of data overload, it is paramount that enterprises harness the relevant data to drive a competitive edge. While the Internet is saturated with over 500 published points of view on the topic of data and analytics, even that is an extremely conservative yardstick for measuring the exponential growth of data pools/availability.

Figure 1: Percentage of respondents from an Accenture survey who plan to adopt data and analytics between 2017-22

High-growth organisations have started tuning in to the need for change, and the need to address the driving forces of change. 1 These range from introspective motivators - Human capital management, process and technology optimisation, to market forces such as the evolving Customer profile and expectations for more digital, real-time, and personalised offerings. The market place is abundant with an ever increasing number of digital disruptors, clearly signalling the urgency for enterprises to pivot from the old ways of doing, to the new ways of being.

As technology giants continue to disrupt the market with their tailored messaging and offerings, they give way to new norms in customer experience delivery from companies. Concurrently, customers have also become increasingly comfortable with sharing their data in exchange for personalised experiences. Singapore, for instance, was ranked 2nd in the world in terms of consumer’s readiness for hyper-personalisation according to the recent Accenture Engage Me Index. 2 These trends have therefore given rise to the expectation from customers to expect of companies to deliver a customer experience that reflects some sort of intimacy with their behaviour, preference and needs. Beyond all this, while the “Why” of creating a data-driven organisation is clear, the question of “How” prevails.

Figure 2: Leveraging data-driven insights (Top 4 plans) – percentage of “high-growth” respondents from an Accenture survey who plan to leverage data and analytics in the following ways between 2017 – 22

High-growth organisations are aware of the “How” to leverage data and analytics, i.e., to derive insights, predict demands, influence customers based on past behaviour, and monetise data. 3 The real challenge, which is also where many organisations flounder, lies in the execution.

Becoming a data-driven organisation can be likened to scaling a mountain; the “How” is hyper-critical. First-time mountain climbers need mountaineering guides, and Accenture is the experienced transformation sherpa for organisations striving to be data-driven. Here are the three things that all organisations at the base camp need to get right.

Fuelling for the climb: Getting the right data

If mountain climbers do not have enough food, or indeed, food with the right nutrients, they risk not having the fuel to power their summit ascent. Similarly, without the right volume, or types of data, even the best machine learning models will yield weak insights.

Beyond acquiring data, organisations can also create new offerings to collect new data, or partner with data exchange ecosystems that add value to all involved. In 2015, 3 out of 5 higher performing companies were already using 7 or more types of data, compared to 1 out of 5 of their lower performing peers. 4 We expect these numbers to rise continuously, especially as industry leaders are compelled to engage in a battle of wits against technology giants such as Alibaba and smaller yet nimbler data and analytics-driven entrants, whether or not they already pose a threat.

Figure 3: Multiple data sources - Percentage of respondents from an Accenture survey who are already leveraging more than 7 data sources

The complete toolset: Architecting end-to-end correctly

In tandem with obtaining the right data, organisations need to have the right set of tools for navigating ability gaps and finding the right paths for transformation on the road to becoming a data-driven organisation. In other words, modern, robust data architecture is necessary for handling high volumes, variety, and velocity of data, generating the right insights, and in turn publishing these insights to the right people and systems, to enable the translation of insights into actions and outcomes.

Modern data architecture comprises six key components:

  1. Data Ingestion: Right platforms to ingest data in batch or streaming

  2. Data Storage & Processing: Storing and processing vast amounts of structured and unstructured data

  3. Data Labs: Providing sandboxes to enable data discovery, test and learn

  4. Access & Publishing: Enabling Access to data at speed and efficiently

  5. Data Consumption: Proving reporting, Analytics and search capabilities

  6. Data Governance: Managing data end to end from mastering data, managing definitions, quality to data security

Worryingly, at least half of all global executives have purported that their back offices are not equipped to support the fast pace, digital and customer-facing nature of the front office, 5 and are therefore not confident about the quality of their data. 6 As such, many organisations are unable to unlock the true value of their data if they don’t possess the tools needed to render data usable.

The collective DNA: Adapting your organisation

The last crevasse that stands in the way of a successful transformation is the largest one. Having the right data and technology doesn’t guarantee a successful summit of Mount Data – employees also need to be equipped with the right skills, motivated, and organised in the right roles. Employees need a data-driven mind-set, and an appetite for change that should be embedded into the DNA of the organisation.

A data-driven operating model is crucial to an organisation collectively as a data-driven machine. The right capabilities are required not just in the data division, but across the enterprise. The organisation must also be structured in a way to ensure data-driven capabilities are effectively and optimally distributed, managed, and utilised. Organisations must transform their enterprise to fully adapt and proactively embed the insights from data and analytics to their daily decision-making. Evidently, application is the ultimate lynchpin for success – those who have done so are 4 times more likely to reap significant ROI. 7 To support this, processes must also be re-engineered to enforce an enterprise-wide data-driven behaviour enabling insights-based decision, embedding data in their day-to-day activities.

Figure 4: High performance are 4 times more likely to reap significant ROI as compared to their peers

Every mountain is different: Unique industries, unique playbooks

As every mountain has its unique challenges, there cannot be a one-size-fits-all climbing approaches. Likewise, there is no single playbook for all organisations across all industries for successfully transforming into data-driven enterprises.

This is the first of our multi-part industry-specific blog series. Stay tuned as we reveal the intricacies of mastering data, unlocking the insights that will help you leapfrog your competitors. In the next article, we explore how players in a traditionally bureaucratic industry are leveraging data and analytics to differentiate themselves – welcome to the world of insurance, revolutionised!


1 Omar Abbosh, Michael Moore, Paul Nunes, Vedrana Savic, Discover Where Value’s Hiding, How to Unlock the Value of Your Innovation Investments (Accenture, 2018).
2 Agneta Björnsjö, John Curran, Margaret Schoelwer, Dave Sovie, Dynamic Digital Consumers (Accenture, 2017).
3 Jyo Gadewadikar, Lynn LaFiandra, Brian McCarthy, and David Simchi-Levi, Brian McCarthy, Winning with Analytics (New York: Accenture, 2015).
4 Mylissa Tsai, The Future Belongs to Organizations with Intelligent Operations, According to New Research from HfS and Accenture (New York: Accenture, 2018).

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