Enterprise Information Management: The Foundational Core Of Digital Transformation Success

Paul Lewis

The definition and implementation of digital transformation has become so muddled that no two organizations are focusing on the same strategies and initiatives. Many companies choose to engage in e-commerce and social media to extend their customer base with engaging, personalized, and round-the-clock shopping experiences. Some eye operational efficiencies through the Internet of Things (IoT) and artificial intelligence. And a growing segment is enticed by game-changing insights from analytics and social sentiments.

No matter the digital strategy, data is the foundation of all of these efforts. The customer experience is about understanding clients and offering services that answer their needs. Decision making requires stored knowledge that can be easily shared, secured, and applied. Operational excellence runs on meaningful insight that drives performance and keeps workers safe.

In digital transformation, every change relies on converting data into actionable decisions. According to Capgemini, companies that act on an enterprise information management (EIM) strategy outperform their rivals by as much as 26%.

The EIM difference in digital transformation

A data point by itself may seem unrelated and inconsequential. But when enterprise data is united and managed as one asset, decision makers finally have trusted, complete, and relevant information they need to seize opportunities and avoid risks that were previously hidden in the background.

One of my clients, Pravine Balkaran, global head of IT at Spin Master, one of the world’s largest toy and media entertainment companies, said it best: “It’s about being able to apply standardization and automation to the entire ecosystem to bring value and move the business forward.”

EIM derives new value by incorporating the traditional functions of data, including business intelligence, data science, analytics, data storage and archiving, data stewardship, and data mobility technology. The more data added, the more valuable the ecosystem becomes – without the complexity commonly experienced when searching for potentially valuable data across a diverse set of existing applications.

By applying EIM to the core of its digital strategy, companies like Spin Master are capturing and coalescing data from a variety of sources and turning it into actionable information to drive better decision making, innovate new products, enter new markets, and encourage a more responsive customer experience.

The EIM road map towards rapid creation of new value

Now for the hard part: Putting EIM into action and at the center of your digital transformation business strategy. There are five things you should do now before moving to a more digitalized and data-driven way of doing business.

1. Inventory available information

Most companies believe that their data resides in core databases and a data model of known entities such as claims, transactions, vendors, and suppliers. Although this is a widely used approach to determining the class of your information, it is only a small part of what you actually own. Structured, unstructured, and semi-structured data; log files; conversations; customer sentiment; and real-time information from suppliers and vendors, for example, should be integrated as part of the overall EIM philosophy.

2. Classify your inventory

Data typically can be classified with one or more of these six attributes:

  • Real-time, streaming data, which potentially comes from machines
  • Static data from production databases
  • Valuable data in real time once stored
  • Realizes value over time and as it changes
  • Relevant to a particular government mandate or legislative concern
  • Objective and relative importance to divisions of the overall enterprise, including customers and the business network

With this exercise, you can begin to understand the function that each data point serves and its usefulness in the future.

3. Encourage the business culture to appreciate the value of discovery

Data-driven decision making is not based on blind faith that data always tells the right story. Rather, it is asking the right questions, and knowing how to dig deep into the data helps us make the connections we need to get an accurate picture of the current situation. Once you discover those nuggets of insight gold, data science and advanced analytics can be applied to pinpoint the appropriate solution. Later, you can leverage data visualization tools to communicate findings and proposed action in a format that is quick and easy for all levels of the enterprise to consume.

4. Shift your focus from yesterday to today and beyond

Traditionally, data analysis is an exercise of looking backward to determine the how, what, when, and why an event happened. However, the pace of change in every aspect of the business has accelerated so much, that it’s rendered this retrospective approach to analytics nearly useless. Real-time access to data allows decision makers to know what’s happening in the moment and how it will impact the future to seize opportunities and mitigate risks.

The path to digital transformation is paved with data

The volume of data generated by people across the entire business network – from employee to consumer and everyone in between – represents a veritable trove of information, insights, and inspiration for innovation. But first, companies need to know where to find this data and how to best apply it to everyday decision making. With EIM, data can be broken down and reassembled into a manageable form that is meaningful, outcome-driven, and transformational.

Learn more about how to uncover Data – The Hidden Treasure Inside Your Business.


Paul Lewis

About Paul Lewis

Paul Lewis is the chief technology officer in Hitachi Vantara for the Americas, responsible for the leading technology trend mastery and evangelism, client executive advocacy, and external delivery of the Hitachi vision and strategy especially related to digital transformation and social innovation. Additionally, Paul contributes to field enablement of data intelligence and analytics; interprets and translates complex technology trends including cloud, mobility, governance, and information management; and represents the Americas region in the Global Technology Office, the Hitachi LTD R&D division. In his role of trusted advisor to the CIO community, Paul’s explicit goal is to ensure that clients’ problems are solved and opportunities realized. Paul can be found at his blog, on Twitter, and on LinkedIn.