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TDWI Upside - Where Data Means Business

Digital Transformation: Making Information Work for You

Digital transformation efforts help strategic analytics teams at all types of businesses leverage the information generated to improve business results.

Many companies have embraced digital transformation as one of their business strategies, but quantifying what that means is often harder than it looks. Businesses ultimately want to be more agile and nimble in responding to a changing world so they can meet customers where they are. This is often driven by their overarching desire to increase their profitability and in many cases provide shareholder wealth. As an analytics leader, you must learn what digital transformation means for you and your teams and how you can pivot your activities to meet the strategic challenges.

For Further Reading:

Five Best Practices to Digitally Transform Your Business

What Healthcare IT Leaders Need to Know about Digital Transformation

Data Shows COVID-19 Accelerates Digital Transformation of Frontline Workers

First, you must understand just what a digital transformation is. Breaking the term apart can help. Transformation is defined as the induced or spontaneous change from one state to another. Businesses can go through a transformation either spontaneously (as they watch competitors and peers make changes) or it can be induced (as they start to lose market share, fail to evolve with an ever-changing customer base, or are compelled by the market and their boards of directors). Regardless, transformation requires a from state and a to state. The goal is that the to state is more optimal at driving positive business outcomes.

The second term, digital, generally relates to the utilization of electronic devices, especially computerized technology. The term also includes recording, storing, transforming, and retrieving information.

With this, digital transformation is changing the organization from one state to another through the use of electronic devices that leverage information. Oftentimes, this entails process improvement and process reengineering to convert business interactions from human-to-human to human-to-computer-to-human. By introducing the element of the computer into human-to-human transactions, there is a digital breadcrumb left behind. This digital record of the transaction is important in making digital transformations successful and is the key to how analytics can enable more successful digital transformations.

In a human-to-human interaction, information is transferred from one party to another, but it generally stops there. With the introduction of the digital element in the middle, the data is captured, stored, and available for analysis, dissemination, and amplification. This is where data analytics shines. If an organization stops with data storage, they are missing the lion’s share of the potential value of a digital transformation initiative. Organizations that focus only on collecting data from all their transactions and sinking this into a data lake often find that their efforts are in vain. They end up with a data swamp where data goes to die and never fully realize its potential value. Whether your transactions are supported by your ERP, CRM, IoT, or any other digital platform, your goal is to enable business success through the proper utilization of your information.

When looking for areas where digital transformation can be enhanced by analytics, focus on three elements: timeliness, reliability, and security.

Timeliness

With information generated by digital transactions, the first goal is to ensure that the knowledge garnered does not get stuck between only those directly participating in the transaction. Lessons learned from the transaction should become part of the greater organizational memory.

This does not mean that every single transaction needs to be reported to every person in the organization. It also doesn’t mean that the information needs to be elevated in the same form or at the same velocity to all recipients. Those participating in the transaction need an operational view of the transaction. This needs to happen in real time. The information is the enabler of the human-to-computer-to-human transaction and the speed of that information flow needs to be as quick as it was in the human-to-human transaction. Otherwise, it will be viewed as a roadblock instead of an enabler.

As it escalates to the next level of management, the information needs to evolve to a managerial view. Managers are more interested in anomalies and outliers or data at a summary level. This level of information is no less impactful to the organizational memory but is associated with a different level of decision-making. Managers are responsible for multiple areas of transactions and need to know when they need to jump in and make adjustments or provide additional support on a transactional level.

Their ultimate goal is to be situationally aware of their teams’ activities, but they don’t have the time and energy to be in the details of each and every digital transaction. When outliers are identified, managers need to be alerted quickly but not necessarily in real time. Management decisions generally fall into a category referred to as business real time. Business real time is often defined as between 15 minutes and an hour. If a manager is getting alerted with high-priority information within business real time, the organization can be viewed as highly effective.

As this information escalates to an executive level, it must evolve to yet another level, where patterns over time become more important than the granular detail of each transaction. Directional shifts in these patterns need to be addressed before things get too far off course. Patterns don’t usually appear in real time or in business real time but can start to manifest within days or weeks. Executive decision-making also leverages these patterns to move into predictive analytics where they can forecast how past patterns will influence decisions about the business’ future. Organizations that are not only capturing the data elements but converting those into patterns and communicating changes to those patterns within days are often viewed as effective.

Reliability

At each level of information dissemination, the content of the message is different. Whether it is transactional, managerial, or strategic information, the data needs to be reliable, but the impact of mistakes is different.

For Further Reading:

Five Best Practices to Digitally Transform Your Business

What Healthcare IT Leaders Need to Know about Digital Transformation

Data Shows COVID-19 Accelerates Digital Transformation of Frontline Workers

At a transactional level, speed is paramount. If there is a mistake in the information, an enterprise can quickly take action to correct it.

At a managerial level, speed is important, but the quality of information is also important. At this information level, outliers and anomalies must be identified. These signals are often elevated so that managers can step in and correct issues before they arise. A higher number of false alarms leads to managers who are less likely to take action. If the information is of low reliability, it becomes noise, and managers must expend significant effort in sorting through true and false signals. Highly precise notifications train managers to act and make decisions.

At the strategic level, speed is even less important, but the quality of the information is paramount. It is from these patterns that executives make long-term directional adjustments to business activity. Incorrect information can significantly alter the trajectory of the business and so great care and attention needs to be paid to the information communicated. 

Security

As information is aggregated and transformed from transaction level to strategic level, the implications of the internal decisions grow as does the information’s value as a competitive advantage. Outliers and anomalies can represent significant risks or opportunities. If this information is inadvertently leaked to the wrong people, it has the potential of changing the direction of a transaction or a customer relationship. 

When information patterns are divulged to the wrong people, strategic threats or opportunities can be exposed. This can have a long-term impact on business success.

As each level of information becomes more sensitive, analytics teams need to manage access. Organizations do this at a transactional level by applying horizontal and vertical filtering at the database. With pre-defined metrics that represent outliers, patterns, or forecasts, these often must be locked down and guarded at the report level or in controls around who, when, and where outbound information dissemination occurs.

A Final Word

If your business is going through a digital transformation and is focused on digitally enhancing business processes, don’t let the resulting information go to waste. Focus on how you develop the right structures and processes to ensure timeliness, reliability, and security for each level of decision making so you can magnify your organization’s digital transformation and, ultimately, exponentially scale its strategic targets.

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