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Unlock greater value with a data-driven operating model

3-minute read

August 16, 2022

We all got the memo to be data-led years ago. Effective use of data helps deliver better experiences for consumers, customers and employees; boosts innovation; enhances a company’s resources and drives sustainable growth.

Eighty-eight percent of C-suite respondents to Accenture’s Business Futures research say using forward-looking data is key to their success. At the same time, many companies are democratizing their data. This enables people on the edges of the organization to access data and make critical decisions, while staying in sync with corporate strategy. This approach helps companies get ahead of changing customer trends and market volatility by boosting speed and agility.

So, the potential benefits are obvious. Why do so many companies then struggle to make it happen? In my experience, the culprit is often a poorly designed operating model that buries data insights under complex organizational structures and bureaucracy.

The value that enterprises generate from their data is still low, with only 32% of companies realizing real benefits. I have had countless conversations with executives who are frustrated by a lack of collaboration between the data and analytics teams and the wider business. Many companies have invested millions in recruiting data experts but still struggle to deliver tangible business value.

We typically find five culprits most often to blame. First, data and analytics are often siloed, without a clear reporting line to the C-suite. Second, companies fail to embed analytics into core work practices or the “moments that matter.” Third, there aren’t enough joint investments across the business. Next, there is a lack of collaboration between analytics and the business. Finally, the approach to talent and recruitment is disjointed.

Eighty percent of C-suite executives said they plan to increase spending on technology in the next year with analytics and artificial intelligence (AI) among the top three priorities.1 However, maximizing return on that investment can require re-configuring the organization and ways of working. For example, one consumer goods company brought together over 20 senior leaders from across all major business functions to agree to a new framework and operating model for collaboration. The goal: to unlock the power of their data.  

In today’s business climate, effective use of data is an imperative. But to succeed, companies need to look beyond investing in the latest technology or hiring the hottest talent.

Realizing value

Business leaders can take these five actions to start realizing greater value from their data.

Elevate to the C-suite. Data and analytics need to have the focus, sponsorship and mandate of leadership. Successful companies are more likely to have formal senior sponsorship for their data strategies. The C-suite must take shared accountability for helping ensure data is used to inform strategic decisions and to improve collaboration between data scientists and the business. Too often, data lacks the right level of influence at the leadership table.

Capture the moments that matter. Companies are drowning in data. To extract meaningful insights, they must be able to identify the “moments that matter” where they can embed analytical solutions to help improve business processes. Imagine you’re in sales in a telecommunications business. In this case, a moment that matters is understanding the churn rate of customers. Insights should reveal patterns so that problematic processes or service weaknesses can be identified and fixed. This needs to be done seamlessly instead of bolting on additional analytical reports or solutions.

Invest jointly. The C-suite member responsible, whether the chief technology officer, chief digital officer or a chief data and analytics officer, needs to convince their counterparts to assign the right level of funding for data and analytics initiatives. These initiatives must be driven by tangible business needs. Data and analytics teams should focus on supporting agreed business goals and avoid curiosity-driven experimenting.

Incentivize collaboration. Most operating models today fail to optimize collaboration between data teams and the business. What if collaboration was linked to performance reviews and incentives? For example, if you’re a customer service manager and you haven’t used data to make better decisions, it could affect performance reviews and remuneration. The same principle would apply if the data team doesn’t receive positive feedback from their business partners.

Approach talent differently. In a competitive job market, data scientists are a precious commodity. Many are recruited from digital natives like Netflix or Amazon — companies that inherently understand data. When they join more traditional industries, they need to use their skills in a new context. This requires a “translator” who understands the industry and its customers. This blend of technical and business know-how is vital. Businesses also need to upskill their workforce across the organization so that there is a better understanding of data and how it can help achieve business goals.

Unlocking insights

In today’s business climate, effective use of data is an imperative. But to succeed, companies need to look beyond investing in the latest technology or hiring the hottest talent. They need to carefully design an operating model that unlocks the insights and business value that data can drive.

Getting it right means combining key capabilities in the right combinations— not only in data and AI, but also in organizational design, talent and culture.

Please contact me to find out how we can help you find the hidden insights in your data.


Samuel Holmes

Managing Director – Accenture Strategy​