How to Accelerate Data-Driven Decision-Making?

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“Data leaders need to optimize and streamline data collection and storage and unlock any legacy data to lay the foundation for maximizing data-driven decision making. Once data can be trusted, more sources tapped, and users can access it more easily – every process can be optimized to accelerate data analysis.” — says Helena Schwenk, Market Intelligence Lead at Exasol, in an exclusive interview with Enterprise Talk.

ET Bureau: The pandemic has shown us that business conditions can flip extremely quickly – why is a robust data analytics strategy crucial to crisis recovery?

Helena Schwenk: As the world continues to contend with the COVID-19 pandemic and its profound impact across different regions and industries, organizations are looking for ways to safeguard their people and customers and their business’ long-term future.

The ability to make timely, right decisions will be critical to how well businesses survive this widespread crisis. Besides, it will impact how well they can position themselves on a future profitable growth trajectory when things begin to return to a “new normal”.

That said, decision-making becomes more perplexing during periods of stress, specifically where there is uncertainty. To remain successful, data must underlie every business phase, providing critical input to readjust plans and predictions, guide, and automate decision-making.

Therefore, it’s critical that organizations have a robust data and analytics strategy in place that maximizes what they can do with the data – using it to its full potential on their road to recovery.

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ET Bureau: What data infrastructure changes should organizations make to help them make data-driven decisions?

Helena Schwenk: We recently surveyed technical decision-makers, and 51% believe their data infrastructure will need improvements to help them recover from macro and microeconomic challenges. Roadblocks include security concerns, data quality, deployment and scaling difficulties, and overcoming data siloes.

To address these challenges, data leaders need to optimize and streamline data collection and storage and unlock any legacy data to lay the foundation for maximizing data-driven decision making. Once data can be trusted, more sources are tapped, and users can access it more easily, every process can be optimized to accelerate data analysis.

Transforming from a legacy infrastructure is, of course, no mean feat, and building a hybrid cloud architecture suited to the requirements of your organization needs careful planning and commitment. However, this shouldn’t stop businesses from embarking on their journey.

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Embracing the flexibility of the cloud can help organizations make faster data-driven decisions. The capability to rapidly onboard new data and provide access to real-time insights will continue to grow in importance. This is where cloud flexibility will play its part if organizations are looking to scale-up their data infrastructure.

A cloud is a powerful tool for allowing large numbers of people to access large volumes of data in real-time. It improves the ease of access and shareability of data and increases agility and flexibility. This means businesses can turn data into value faster than ever before and quickly adapt as the market and broader economic landscape evolve.

Combining and analyzing data from various sources into a centralized high performance, in-memory cloud-based data platform will allow the numbers to do the talking. This foundation will enable businesses to solve complex challenges and run smarter—driving change with actionable insights at fast speeds.

One organization that is fulfilling its data potential is Revolut. As one of the UK’s unicorn companies, it is no stranger to explosive growth, with data volumes growing 20-fold within 12 months. Such change made the maintenance of 800 dashboards and fielding over 100,000 SQL queries daily very challenging.

By acting as a central data repository, the database has saved time across multiple business units and can now resolve queries and reports in seconds instead of hours. According to Revolut’s data scientists, these query times are now 100x faster than their previous solution.

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Moreover, every employee has access to this repository as a “single source of truth”. This data is available for interrogation, too, with business intelligence (BI) tools and self-service access available to everyone instead of just the data scientists. Key performance indicators (KPIs) were based upon this data and standardizing performance goals for everyone across the entire organization.

As a result, Revolut has defined tens of thousands of micro-segmentations within its customer base, built ‘next product to purchase’ models that increase sales and customer retention, and delivered granular personalization to over 13 million users.

ET Bureau: Are organizations doing enough to educate their entire workforce on the benefits of being data-driven, or is the data skills gap still commonplace?

 Helena Schwenk: It’s paramount that employees at all business levels have access to data to make faster, better decisions and uncover new opportunities. According to our research, only 32% of data decision-makers said that their data teams could extract the insights they need.

From this, it’s clear that organizations can do more to educate their workforce on the benefits of being data-driven. Sure, businesses recognize the potential of data and its role to improve business performance, but they can invest more in deriving actual value from it.

When it comes to data, a business-wide mentality is imperative – everyone has to be on board to maximize the benefit. Organizations can make their data strategy even more effective with the democratization of data. Suppose every employee across an organization can gather and/or analyze data with intuitive tools. In that case, faster and better business decisions can be made by the people driving the organization day-to-day.

Gartner has predicted that the number of these ‘citizen data scientists’ will grow 5X faster than the expert data scientists through 2020. This is because more organizations recognize that leveraging citizen data scientists can effectively bridge the current skills gap.

ET Bureau: Is this why we’re seeing the rise of the Chief Data Officer? What skills do they need?

Helena Schwenk: The above data skills gap has led to a growing number of Chief Data Officers (CDOs) taking charge and developing their organization’s understanding and data usage.

They bring people together to help them apply data insights to business operations and drive the business forward on multiple departmental levels – advancing innovation, operational efficiencies, and revenue growth.

This puts businesses in good stead to effect change with a data-driven, people-centric enterprise-wide approach – both during the crisis response and in the future.

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However, while the need for CDOs is music to qualified for the role’s ears, it’s also where the biggest issue lies; there is not the talent available – globally – to meet the increase in demand. Fortunately, the talent pool is more comprehensive than many may think. Three essential CDO skills aren’t essentially what you will expect.

It’s not all about data – CDOs do not necessarily need to be from a pure-data background. They need to be strategists and skilled in answering challenging questions and ensure actions derive business value. Basically, candidates might come from business intelligence and operations, problem-solving, finance, or marketing backgrounds because of their ability to deliver a more in-depth business situation analysis.

Become a change agent – The drive towards a data-driven approach is most likely to meet with resistance, especially when it threatens the status quo, individual power bases, and potentially contradicts closely held beliefs and practices.

They must actively work to understand the business’s problems and identify how data can support it. This would require the CDO to demonstrate value quickly, build empathetic relationships, and overcome potential conflicts.

Interpersonal skills are an indispensable part of the new skillset for data scientists today. Sell, sell, sell – They are required to sell their insights internally – the ability to tell stories is a vital skill of a CDO: a story makes the benefits of data precise for those who may be turned off by hard statistics.

In some of the most successful organizations, CDOs have also been known to use their interpersonal skills to recruit the ‘data citizens’ mentioned above from different departments to make the tactical use of data more entrenched across the business.

This can help in making data an open and useful tool, instead of a confusing gated asset that can be accessed, understood by a few people – bridging the data science skills gap.

Helena Schwenk is the Market Insights/Intelligence Lead at Exasol. She specializes in technology trends, competitive landscapes, and go-to-market strategies. She uses this knowledge to keep Exasol’s marketing, sales, and product management teams fully connected to the wider industry landscape. She has over 24 years of experience working in the data analytics field, having spent 18 years as an industry analyst specializing in Big Data, Advanced Analytics, and AI. Also, 6 years as a former data warehousing and BI practitioner