The Bad Habits To Break Now: Data & Analytics Leaders

This is what the professionals want you to stop doing.

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Whether you’re back in the office or still working from home, one thing’s for sure: we’ve never been more reliant on access to news* than we are right now (and by news, we mean factual insights). While your company may have Zoom and Teams working, it’s entirely possible that the multi-year digital transformation is causing problems. Whether it’s senior executives expecting data nirvana, business teams forgetting to proofread briefs (or document requirements), or data teams replying in code, this is what the professionals want you to stop doing.

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Table of Content

1. Problem 1 - Not Having A CDO (Or Keeping One!)
2. Problem 2 - Not Linking The Data Strategy To The Business Strategy
3. Problem 3 - Not Prioritising Data Literacy
4. Problem 4 - Confusing Everyone
5. Problem 5 - Responding With Dashboards (Instead of Answers)

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Problem 1 — Not Having A Chief Data Officer (Or Keeping One!)

Fact — The CDO role has one of the highest turnover rates in the C-suite.

Alarmingly — in a 2020 study by MIT Sloan — less than 30% of executives report that the CDO role is successful and well established within their organisations.

Case in Point: Several major banks are on their fourth or fifth incumbent in the CDO role, and others have paused to rethink the role, highlighting the challenge that CDOs face. As such, the long-term outlook for the role of the chief data officer remains uncertain.

Although it has been noted that data-driven companies like Amazon and Google have not traditionally appointed CDOs because data is already deeply ingrained in their DNA — most companies are not like Amazon or Google.

Solution 1 — The establishment of the chief data officer role (or similar) represents a recognition that data matters to the organisation.

Organising, governing, and delivering value from data is one of the primary factors that differentiates companies that seize the moment from those companies that lose their way, especially in the digital economy of the present and future. Therefore, companies must ensure that the chief data officer has the necessary tools and support for executing on his or her data vision. Only then will businesses be able to legitimately claim that they have earned the right to be called data- driven.

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Problem 2 — Not Linking The Data Strategy To The Business Strategy

Fact — Most data strategies have nothing to do with the business strategy.‍

MasterCard CDO JoAnn Stonier advises that for companies to be data-driven, “the data strategy of a company must follow the business strategy.” Similarly, Arti Zeighami, Global Head of Advanced Analytics & AI H&M Group, shares that he doesn’t pick AI use cases — instead, he solves business challenges that his colleagues have.

Since each organisation is different, embodying its own business objectives and culture, companies must commit to a data strategy that reflects the relevant use cases, supply chain of data, and data consumption patterns that drive business outcomes particular to them.

Solution 2 — Develop and execute a data strategy that mirrors your business strategy and vision.

Problem 3— Not Prioritising Data Literacy

Fact — There is a lack of desire from employees to be data-driven.

Although numeric skills are important to avoid deception and to function in society, it’s challenging when most people tend to avoid quantitative methods and even fear them (Slootmaeckers et al, Politics, 2014). In fact, according to Accenture (2020), only 21% of the global workforce are fully confident in their data literacy skills — i.e their ability to read, understand, question and work with data.

So how can we help employees acquire numeric and statistical skills?

Solution 3 — Embrace self-service business intelligence, i.e. business friendly tools that are truly designed for real-time, self-service data consumption AND create a compelling career path for data leadership across all levels within your organisation.

In the 2020 MIT Sloan Review report, Bank of China’s Goldberg described the “need to create a career path to enable the business to embrace data.” This entails building systemic capabilities among all functions relating to data, including strategy, governance, architecture, analysis, and consumption. Goldberg noted that by executing consistently, an organisation will come to “embrace data as a business asset.”

Bob Darin, CDO of CVS Health, observed that coordinating across the enterprise is one of the biggest challenges for the CDO and noted that his role “entails a significant amount of change management — it is the biggest part of the job.” - MIT Sloan (2020)

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Problem 4 — Confusing Everyone

Fact — The context, complexity and value of data is lost on everyone.

According to the MIT Sloan report (2020), data brings value to the extent that its benefits are clearly articulated and understood throughout the organisation. Many data initiatives fail to succeed due to the complexity of managing data and the failure to communicate business value in clear ways that cut across business and technical boundaries. For data leaders, communication is key: Speak in business terms, and avoid technical jargon. Communication is key to engender trust in your data to assure business and customer buy-in, credibility, and momentum.

Many data initiatives fail because business teams lose faith in the data. Factors that might lead to such distrust include incompleteness, inaccurate or misunderstood representation, or a lack of common understanding and definitions. American Express’s Crop observed, “The future of the CDO role is about enabling trust in data and driving innovation. CDOs must engender that trust in data.”

Solution 4 — Relentlessly communicate the context, complexity and value of data up and down the organisation.

Problem 5 — Responding With Dashboards (Instead of Answers)

Fact — People need answers, not dashboards.

You want to drive data adoption. But many people don’t know how to use data, and even when they do, it can be difficult to access. Building dashboards sounds great in theory. But terrible if you want to rapidly iterate. Here are the facts.

On top of this:

• 30–40 percent of reports that businesses generate daily add little to no value: Some are duplicative, and others go unused, with the result that considerable resources are wasted. — McKinsey 2020
• Dashboard rich. Insights poor: Dashboards aim to deliver insights — but visualisations alone are only one part of the insight equation. Without context, knowledge or the ability to drill down or see the business from all angles, visualisations are meaningless.
• Stuck waiting for data nirvana: Traditional BI delivery models are still suitable for many situations, but they don’t offer the agility and efficiency that quickly changing business requirements demand — leading to high response times.
• Analysts drowning in requests. Hands tied by resource constraints: Not having enough resources to cope with demand for analytics, leads to the ever-growing problem — “we have data, but no one can get value out of it”.
• Pressure to reduce costs. Without jeopardising growth: With pressures from C-suite to run leaner, the cost of data & BI teams is a huge focus. Organisations need to ramp up data efforts while managing costs.

Solution 5— Best-in-class companies don’t wait until their five-year digital transformations are complete before thinking about streamlining data consumption. Instead, they make their business-intelligence capabilities available to employees on a self-serve basis from the start. Only then will they be placed to accelerate solutions that will fuel growth. Hyper Anna makes it possible for people across your business to access data insights, without a degree in data science.

Conclusion

Data and Analytics leaders need to be equipped with the right support so they can execute on the company’s business strategy and data vision. And unless tools, processes and leadership combined address the real needs and motivations of employees, becoming data- driven will remain a challenge.

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