CHAPTER 5

THE ROADMAP

A roadmap is a plan for people, process, and technology initiatives over the short, medium, and long terms. In all likelihood, the information governance program already has a roadmap that covers initiatives over the upcoming 18 to 24 months. Given the increasing importance of big data and its visibility to senior management, information governance programs need to include it within their roadmaps.

5.1 The Roadmap Case Studies

Case Study 5.1 describes a large pharmacy benefits manager that developed an integrated roadmap for information governance including big data.

Case Study 5.1: An information governance roadmap at a large pharmacy benefits manager

A large pharmacy benefits manager appointed a chief data officer who reported to the chief operating officer. The chief data officer appointed a director of information governance with responsibility for treating information as an enterprise asset. As shown in Figure 5.1, the director of information governance established the following roadmap in consultation with the council:

• Months 1-30—The information governance program focused on master data for patients, prescribers (doctors), and drugs (medicine). The program trained stewards within the business to manage these master data entities.
• Months 12-30—The information governance program focused on reference data for key diagnosis and procedure codes, known as ICD-9 and CPT codes. (These codes are discussed in more detail in chapter 6.)
• Months 31-48—As of the publication of this book, the information governance team had decided to also include big data within its overall roadmap. The pharmacy distributor selected two big data types:
  • Big prescription transaction data—The distributor managed millions of prescriptions each year. These prescriptions had to be correlated with patient and drug master data to avoid adverse reactions between drugs.
  • Social media—The distributor also wanted to understand overall sentiment analysis to address any adverse comments and sentiments about the company and its marketing practices within social media. However, the company moved social media further out in its roadmap due to an uncertain regulatory environment from the U.S. Food and Drug Administration. Case Study 13.3 in chapter 13 describes these regulations in detail.

Figure 5.1: A big data governance roadmap at a pharmacy benefits manager.

Case Study 5.2 describes a very preliminary roadmap for big data governance at the treasury division of a large financial institution.

Case Study 5.2: A big data governance roadmap at the treasury division of a large financial institution

The treasury division of a large financial institution offered integrated cash management and liquidity management services to large and mid-size corporations. The enterprise data architect was the initial sponsor for the big data program. As of the publication of this book, the division was very much in the early phases of rolling out a big data program. However, the initial roadmap for big data governance is shown in Figure 5.2. Here is the architect’s thought process behind the roadmap:

• Months 1-6—The enterprise data architect spent the first six months laying down the technical infrastructure for big data. The architect focused on acquiring Linux servers and an Apache Hadoop distribution. When asked about alignment with the business, the architect responded, “In a traditional IT project, I would definitely focus on upfront alignment with the business. However, since big data is so new, I will have a hard time putting a viable use case and financial justification in front of the business. That is why I am so focused on laying down the infrastructure to start showing some small, but real, results. Hopefully, that will drive greater buy-in and funding from the business going forward.”
• Months 6-12—The architect wanted to bring in detailed transactions to analyze a snapshot of daily positions. The financial institution had never conducted this level of granular analysis in the past, due to the high cost of legacy infrastructure.
• Months 12-24—The architect wanted to bring social media and other unstructured content into the Hadoop environment. Given that most of the financial institution’s customers were large corporations, the architect was exploring unstructured content such as 10-K and 10-Q filings by counterparties.
• Months 24-36—The architect felt that the financial institution would be in a position to govern big data only after 24 months. The treasury division already had an existing information governance program focused on the master data relating to its large corporate customers. The operations group was the business sponsor for this program. When asked why the big data initiative was kept outside the auspices of the information governance program, the architect responded, “We believe that it will take a few years before the big data initiative starts producing results, and we can engage the business.” Having said that, the architect recommended that the organization think seriously about all the traditional aspects of information governance:
  • How do we move data in and out of Hadoop?
  • What about data quality in Hadoop?
  • What about metadata for big data?
  • How do we integrate big data with the master data management repository that we will be rolling out over the next 12 months?

Figure 5.2: A big data governance roadmap at the treasury department of a large financial institution.

Summary

It is highly likely that senior management will be willing to fund at least a pilot project around big data, given its high visibility within the mainstream media. As a result, the information governance team needs to update its roadmap to include the people, process, and technology initiatives associated with big data.