Seven Lessons in Closing the Gap Between Data and Revenue

GoodData is a Business Reporter client.

Here’s how governed and trusted enterprise-wide analytics have the power to drive adoption and skyrocket growth.

Earlier this year, GoodData surveyed 100 IT executives on their current and future data and analytics priorities. The majority (85%) of those surveyed agree that a weak insights delivery layer hampers their ability to scale their analytics programs. As a result, it’s likely their business is impacted.

We’ve all heard how data is the new currency; after all, everyone is collecting and measuring something. So, why is it increasingly difficult to provide consistent insights and analytics across an entire organization, business and customer base?

GoodData solves this problem. We help companies small and large to fill the gap in consistent insights and analytics and to build revenue from their revitalized analytics. This is what we’ve learned:

1. Data as a service is the next frontier in cloud infrastructure

Cloud has ushered in a modernization wave for data storage. But how do you access data stored in data lakes or warehouses? How do you make sure the right internal and external users have access to the data pipeline?

Here’s how: Data as a service (DaaS) provides real-time, governed, scalable, global insights and analytics both inside and outside of a company—and cloud infrastructure enables DaaS. In this way, the most innovative businesses have the infrastructure to deliver insights better, faster and at a reasonable cost to whomever needs access.

2. Commitment to data starts with leadership

Across business operations, a lack of strategy leads to lack of investment and return—thus drying up support for future investment. A successful data strategy requires support systems and solutions to work efficiently and effectively.

The more a company invests in data—with both capital and culture—the easier it can be to turn data from a cost center into a revenue generator. The most successful and innovative companies are managing increasing amounts of data to gain an edge. Data should be seen as something that can empower teams, and that vision needs to come from the top.

3. Data-driven business is more complex than a desktop visualization tool or spreadsheet

As the proliferation of data accelerates, companies cannot become complacent about how they’re leveraging it. Having access to data via IT teams or complex software isn’t enough. To become a data-driven business, and to stay agile and competitive long-term, companies must chart a path forward that makes actionable insights readily available to the entire organization, and ensure that every decision can be a data-driven decision.

4. Data literacy shouldn’t require a data science background

Decisions are made across all parts of a business. It’s tempting to hold data scientists responsible for data literacy. And, of course, technical teams should still know how to understand data.

But not everyone at an organization needs to be able to interpret formulas based on a CSV file. For analytics to be truly transformational, every user must have access to data in a format they understand, augmented with semantic information. If your analytics solution presents the data in a simple way with accessible storytelling, anyone at a business can tap into its power.

5. Traditional business intelligence is the new shadow IT

In layman’s terms, shadow IT is the result of businesspeople solving their data problems outside of the IT organization. This is what the majority of business intelligence (BI) is today: a network of flash drives and personal cloud storage full of spreadsheets and CSV files. BI also depends on desktop tools paid by personal credit cards and boutique consulting services paid from departmental budgets.

It’s true that protective data management is at a minimum. The value in taking BI outside of IT lies in flexibility. But for the company as a whole, that flexibility proves to be an inhibitor. The widespread usage of desktop tools results in countless versions of the truth; everyone defines the data in different ways, and discussions end up having different meanings, resulting in faulty decision-making.

6. Successful analytics demand a balance between governance and flexibility

Early BI efforts were run entirely by IT, while today’s BI is a free-for-all. We swung the pendulum from one side to the other, yet neither has fully worked.

The right answer is in the middle: The future of analytics must allow everyone to leverage data in the cloud to build their own personalized dashboards, create insight applications and, most importantly, share and collaborate; the future of data depends on collaboration between IT and business teams. IT will focus on governance, consistent business rules, data asset development, accelerated response and real-time data, and businesses will have the freedom to innovate with low-code/no-code analytics tools.

7. Investing in composable analytics—the last mile—is a game changer

True data companies have a balance between complex BI tools that IT and data science teams can leverage for long-term planning, and simpler tools that provide business users across the rest of the company with clean and consistent data insights.

Today, most companies have invested in the former. However, top data and analytics companies are outperforming the competition because they’ve invested in the last mile of analytics: where employees at all levels are empowered to make data-driven decisions and the company as a whole is nimbler and more innovative.

Consider one particular client—an e-commerce company with over 2,500 brand partners that need insights about how the company’s 32 million active customers behave on the platform. It partnered with GoodData to provide relevant and timely insights, such as which products are selling where, to whom, and why, allowing brand partners to maximize revenue, grow market share and create new revenue streams from data they collect. When the client’s brands are successful, so is the platform itself. As a result, our client was able to conquer the last mile.

A unified analytics stack drives growth

With the right data and analytics tools, organization-wide access is possible. A unified analytics stack—using the same platform to power both internal analytics and analytics as a product—is revolutionary. And that’s exactly what GoodData does. Companies that truly enable and embrace data across the organization will yield its most valuable benefits: profitability, efficiency and an improved customer experience.

Want to learn more about data as a service? Request a custom demo with one of our data engineering experts.

—Industry view from GoodData

This article originally appeared on Business Reporter. Image credit: iStock–id1199010148