Capitalizing on digital transformation opportunities with analytics isn’t something that can be achieved by merely capturing, storing, and processing more data. Real, lasting change comes from turning that data into trusted, timely, and actionable insights that drive growth and profitability.

More than ever, businesses of all sizes are acquiring vast amounts of structured and unstructured data at extraordinary rates. In fact, worldwide, quintillion bytes of data are produced every day through a stunning range of digital sources, devices, transactions, and networks that connect to, among other things, people, objects, and devices.

Every email; social media post; text message; online search history; app interaction; and financial, consumer, and healthcare transaction contribute to data volumes that are larger than anything we’ve seen before. It’s often estimated that nearly 90% of the data we have today was generated just in the last few years. This same volume, velocity, and variety of data collection almost equally apply to business transactions.

However, we often overlook the presence of disconnected and fragmented data silos – making it impossible to paint a complete picture of the business because different segments linger in detached states or isolated buckets. Left disintegrated, these data buckets rust in data warehouses and lakes – unless they evolve into cohesive and compatible building blocks that form the foundation of an intelligent enterprise.

Here are the top 10 reasons why analytics-driven digital transformation requires businesses to go beyond generating more data.

1. Data empowers us to make better-informed decisions, but not necessarily better decisions

The concept of “better-informed decisions” is distinctly different than the concept of “better decisions.” History is filled with examples of leaders making “bad” decisions, even with access to an ample volume of data.

Better-informed leaders don’t always make better decisions. However, better decisions almost always start with better-informed leaders.

2. Access to more data is useless when we do not ask the right questions

Having more data doesn’t do much good if we aren’t asking the right business questions or don’t understand the assumptions behind them.

Through critical thinking, we need to carefully examine evidence based on what’s relevant to the question before reaching any conclusions or making any decisions. That starts by asking questions, which is a prerequisite for asking the right questions.

3. Leadership is the ultimate driver for success with enterprise data, even if we don’t have more of it

The process of creating value with data begins and ends with business leaders who promote a culture of data-driven decision-making. When it’s absent, we lose direction and guidance and cannot make a significant impact.

Leading by example, data-driven leaders are eager to not only consume data, but also apply insights derived from data assets to make decisions that matter. This experience demonstrates firsthand a mindset that sets an example for the rest of their teams. By recognizing data as a strategic asset, they provide a clear and consistent message for everyone to follow when delivering business outcomes.

4. Business intelligence platforms make better-informed decisions possible, but can’t guarantee them

Coupled with the right technology, the ability to design, implement, and manage enterprise reporting and analytics platforms can deliver a fundamental aspect of business intelligence: Insight into the right data, for the right role, and at the right time.

At the same time, our teams’ talent plays a more pivotal role than technology. Their passion, regardless of the challenges they face or the resources available to them, will be the determining factor, not technology alone.

5. Enterprise data is ineffective without an integrated strategy and governance

Generating reports on any data—big or small—isn’t synonymous with delivering better-informed decisions. An integrated enterprise data strategy, strengthened by unified data governance, is not a nice-to-have option, but a must-have requirement.

Data governance is often misunderstood as a process of data control and authorization. Instead, it represents a core foundational block of an enterprise BI strategy that can’t be ignored nor taken for granted if we want to deliver secure, trusted, and consistent data insights. And it can’t exist separate or independent from an organization’s business or technology strategy.

6. To deliver value with business data, we need to put quality before quantity

As we evolve as a society with rapid and infinite points of data consumption for personal connections and experiences, we seem to take quality for granted and choose to focus more on quantity. We may argue that a similar trend may be diluted in the business world, where we assume that quantity can make up for quality.

It’s true that we can achieve greater depth and perspective as quantity increases. But by the same token, data for the sake of data doesn’t help us either. Quality must come before quantity!

7. If we can’t trust our data, we won’t use it—no matter how much we have

Speaking with hundreds of colleagues and customers with a wide variety of backgrounds and industry experience, I know that a lack of trust in enterprise data is a frustration that’s prevalent in most businesses. In some cases, it is spread across the entire enterprise.

This reality breeds a lack of conformity and standards that are required to power comprehensive data-driven decision-making. Data quality must be a top priority and a key component of promoting the mindset that views data as a strategic asset, starting with leadership.

8. If it’s not timely, it’s too late

Businesses can no longer afford to wait for traditional transformation cycles that churn data for days or weeks. Leveraging new technologies—such as cloud, mobile, and in-memory computing—are fueling this paradigm by demanding more data points faster and elevating the value of real-time analytics for in-the-moment insights and business outcomes.

9. Data in the wrong places is just dark and dusty data

In its purest form, “dark data” remains unreachable and unexploited for greater business value. But “dusty data” is more nebulous, where being captured in the past has gone unused or overlooked.

Both kinds of data continue to pose a challenge for organizations that seek to extract insights from vast amounts of data deposits in their enterprise vaults. Raw data extracted from transactional or operational repositories doesn’t automatically generate value, unless it is transformed to provide different context and diverse points of consumption.

10. We can’t drive value with data if we don’t know it exists in the first place

In real estate, success is guided by the mantra “location, location, location.” When it comes to data and analytics, I say, “communication, communication, communication.” We need to effectively inform and educate our stakeholders about our portfolio of analytics and reporting capabilities.

Think about it: If users don’t know if data exists, can’t find it easily, nor access it quickly, how can they consume it?

This is where establishing a single point of access plays a crucial role. By using a central hub that serves as a portal for all enterprise analytics and reports, we can simplify access. This single point of entry to analytics and reporting can pull from on-premise and cloud solutions, as well as any related applications or legacy solutions. The more we train employees them about what exists and how they can access it, the more likely they are to adopt it.

Bottom Line

These insights may seem obvious, but you would be surprised how often they are overlooked or taken for granted.

More data doesn’t merely guarantee better decisions. Instead, data must become a conduit for delivering timely and actionable insight to influence or shape business outcomes.

Only then can we realize the promise of digital transformation through analytics: delivering trusted, timely, and actionable insights that enable faster, better-informed decisions and drive growth and profitability.

Remember: Digital transformation isn’t a technology makeover—it’s a business revolution!