Accelerating Enterprise Digital Transformation with a Next Generation Database

Chapter 1. Enterprise Digital Transformation and Business Growth

Enterprise digital transformation describes a new way of thinking about business. In many ways, this transformation turns things around, from product-centric to customer-centric, with a focus on value throughout the organization. Big data and the ability to capture a steady stream of insights from many disparate sources simultaneously are important drivers of enterprise digital transformation.

This transformation is not merely a new way of increasing revenue or cutting costs. Rather, enterprise digital transformation is a fundamental and foundational change to the way business is conducted. Central to the transformation is how data is ingested, consumed, processed, and analyzed.

No discussion of change in business would be complete without looking at the fundamental worldwide changes that began in 2020 and continue today. Organizations that positioned themselves with cloud native technologies were well-placed to thrive in the new environment because these technologies made transitioning to remote work seamless. These organizations didn’t need to migrate complex on-premises infrastructure to the cloud, and adjusting capacity to respond to new demands was a primary architectural component of their existing cloud native deployments.

Many of these changes will permanently alter how business is conducted, and the pace of change also enables organizations to add capabilities faster than ever. This chapter examines the modern digital enterprise and how business is moving forward thanks to the digital transformation.

Driving Business Growth

A primary driver of growth in business is a change in the business environment, whether driven from inside the business or through external forces. Whether that change presents an opportunity or poses a threat depends largely on how well the organization is positioned to react to the change. In many cases, changes in the business environment present an opportunity for increased profits through competitive advantage.

The mere existence of an IT function within an organization was itself a competitive advantage in the early days of computing. Those organizations became more efficient and in many ways became faster than their competitors at identifying new opportunities. However, computing resources were quickly deployed by other organizations, thus closing the advantages available by simply incorporating computing into business processes.

Fast-forward to today, and organizations are still seeking profits from growth opportunities found through competitive advantage. As before, competitive advantage is short-lived. Finding competitive advantage frequently means sifting through huge volumes of data, but that data is often contained in separate systems that have evolved over many years. Even if the data from these disparate siloed systems can be analyzed in a coherent manner, the data and events that generated the data may be too far in the past to be actionable. Therefore, if a growth opportunity is found, it may be too late to act on that opportunity or bring the opportunity to market.

Unfortunately, bringing together data silos that have grown over many years is a difficult task, sometimes prevented merely by internal politics within the organization. We need a different approach entirely: finding growth opportunities through digital transformation from within the organization, in much the same way that the early IT functions changed the nature of business itself.

Improving ROI

Because of the pace of change, building IT infrastructure to support strategic business initiatives can be costly, sometimes with little return. Cloud-based, on-demand resources help alleviate significant up-front costs that can push profitability into the future. But infrastructure is only one part of the return-on-investment (ROI) story.

Improving ROI means choosing cloud native software that is simple to deploy in a repeatable and reliable way. Repeatable deployment facilitates Agile development methodologies and enables developers and testers to create and use environments as needed without involving infrastructure specialists. This DevOps-centric approach is scalable and further helps reduce the overall investment in technology, thus providing an opportunity for greater returns.

Driving New Revenue Opportunities

Enterprise digital transformation creates opportunities for new revenue streams. Vast amounts of data contain deep and detailed information. Previously, even if this data was captured, the cost of mining for useful and actionable information was prohibitive. Today, data can be captured and analyzed in real time as a stream to reveal insights that would previously have been hidden. For example, connecting purchases and purchasing interest from multiple sources can generate leads for complementary products and services. Collecting the purchasing habits of consumers with similar profiles enables foresight into potential future needs.

Adding Business-Intelligent Services

Enterprise digital transformation enables businesses to deploy intelligent services that take advantage of incoming and already-existing data to make smarter decisions. Rather than building single-use business-intelligence services from monolithic platforms, a business-intelligent service is aware of the available data and aware of the needs of the business. Data is analyzed as it is being recorded and is used to make better decisions but also to build services that are more intelligent.

The digital transformation for business-intelligent services moves the organization from reactive to proactive. For example, predicting future purchases based on a current basket of goods is a problem that has been solved. However, integrating a customer’s basket of goods with inventory and stock levels across vendors while also incorporating sales targets to incentivize the customer to purchase in real time requires a new business-level awareness.

Extending Real-Time Insights

Many AI-related predictive analytics are well-known, and sometimes well-solved, problems. Transforming the predictions into real-time actionable tasks and then doing so at scale is the digital transformation in action. Scaled analytical platforms work well for looking at historical data and then using that history to help predict the future. But being able to create predictions based on incoming streaming data is necessary for a true digital transformation.

Scaling to meet demand is necessary in order to fully leverage insights derived from incoming streaming data that is processed in real time. The amount of incoming data is sometimes predictable, such as when an advertising campaign is going to begin, or the data may follow predictable cycles of increase/decrease. At other times, the amount of incoming data is unpredictable, such as when a social media interaction is unexpectedly picked up by an influencer.

Opportunities that can be found in data, such as a social media post gaining popularity unexpectedly, are missed without the ability to scale up seamlessly to meet demand. Scaling resources down when not needed is itself a vital capability of a modern digital organization. Unused compute and storage resources are costly while providing no tangible benefit.

Scaling simple compute and storage resources is a common capability in many cloud native organizations. However, scaling data-related capabilities is more difficult and requires a hybrid approach that incorporates components of analytical and transactional database architectures. Hybrid transactional and analytical processing (HTAP) also needs to integrate seamlessly in cloud-based architectures rather than having cloud capabilities added as an afterthought. By bringing elements from both analytical and transactional databases, HTAP helps the business become more agile.

Achieving Business Agility

As the use of computing resources within the enterprise has evolved, projects involving technology have also evolved. In the past, projects frequently used waterfall multistage methodologies that involved significant effort attempting to capture all requirements early in the process. Any changes realized in later stages also required significant effort to incorporate back into the project. The end results were late delivery, underwhelming products, and missed opportunities.

Organizations counteracted the long waterfall life cycle with Agile processes for IT projects. The time to market with an Agile methodology is significantly lower, and the resulting product matches the business need more accurately. Rather than attempting to capture all requirements up front, an agile organization embraces change at any point in the process.

Today, organizations are using those same Agile processes across business functions. Doing so enables the entire organization to react quickly, expect change rather than avoid it, and work with a customer-centric mentality. By embracing change, business itself is transformed. The ability to react quickly to changes in the external business environment helps reduce any advantage gained by a competitor. Thinking in terms of customer-centricity enables opportunities to be found that might have been overlooked in the past.

Summary

Enterprise digital transformation is an opportunity for organizations to fundamentally change the way business is conducted. Breaking down data silos, moving toward cloud native technologies, and incorporating Agile processes with industry-leading technologies enables the organization to become more proactive rather than reactive. The digital-first mindset brought by these technologies and processes moves the organization toward the end goal of helping decision makers gain insight based on real-time data rather than historical snapshots.