A few weeks back, I had the pleasure to meet and interact with some of our clients at Think 2018. They talked about where they are in their data management journey and where they would want to be. One major challenge that many of them face is the inability to adjust with the rate of data growth for both existing and new data sources. Through this post I’ll share some best practices through which you could manage your data effectively.

Information governance

Information Governance is not just about the data or the technology that’s used to manage data, it’s about an entire ecosystem within an organization – people, process, and policies along with the data and technology. And thus, creating and implementing an effective information governance strategy is a shared responsibility.

Data is no longer considered the byproduct of business activities. Today, enterprises rely on data analytics and reporting for making business decisions.  In most cases, business activities and processes are driven by data. Thus, enterprises need to think about how to position their data as a corporate asset to mitigate liability risks, and at the same time, leverage their data’s value to derive insights. I’ve always considered data to be an asset when used correctly.

Be confident with your data

An information governance maturity model defines a pathway of improvement for the way an organization stores and manages its data. The following are the five phases of an information governance maturity model. The maturity levels often range from being unsure about how to manage the data to being confident about it. This maturity model can be used for assessing and achieving compliance, by identifying the gaps and planning the efforts, priorities, and objectives to achieve the goals. Many organizations are still on phase one (unsure) and phase two (overwhelmed) where data can seem like a liability rather than an asset.

Figure1: Information Governance Maturity Model
Figure 1: Information Governance Maturity Model

Thus, for any organization to move from being unsure to being confident about their data, they should follow the below four steps:

1. Find and analyze the data: Every organization has data storage in their infrastructure portfolio, which is a basic need to help run the business. Most of them have a refined method to identify and plan for storage purchases. Often, what they don’t plan for is effectively managing their stored data. Their initial infrastructure plan usually does not include potential ROT data such as images, audio files, videos, duplicate data etc.

With stringent regulations for data privacy, it is more important now than ever to understand what data sources you have, what information they hold and what is the value in keeping that data. Thus, the first step to an effective information governance strategy is analyzing your data sources, finding the data that has business value and getting rid of inactive data.

Join us on June 5 to learn the best practices and practical tips

in identifying and protecting sensitive data

2. Classification and relevance: Many organizations have recognized that their data is not stored properly, and it makes it hard to find the data for running Analytics, eDiscovery, Records and other Compliance programs.

Since, every organization stores its data differently, they should define their own classification categories. One should start with the existing data and start to classify it while working towards automated classification for any newly created data.

3. Business process optimization: Organizations need to define new business processes and optimize the existing ones around data distribution and usage. The alignment of business process with the information governance strategy is important to ensure that the technology investments provide the insight needed for organizations to make the right decisions at the right time.

4. Corporate policy enforcement: Any effective information governance strategy must include policies at its center. The initiative starts with well-defined terminologies and business policies, and creating awareness within the organization about enforcement of those corporate policies. The data governance policy does not limit data access but it regulates data usage by ensuring that different data is handled differently and in accordance to the corporate policy associated with it. Thus, governance acts as an accelerator and not a roadblock for an organization. The organizations who have created and implemented retention policies and schedule management for routine disposal of data, have seen significant cost savings.

An effective information governance model lets you:

  • Reduce the data volume and the associated cost and risks with it
  • Respond quickly to upcoming or changing compliance demands
  • Reduce the cost of implementing data policies
  • Reduce the time and amount of data for eDiscovery
  • Deliver a sustainable competitive advantage

Organizations across the board use data to help achieve their goals. The goal of the information governance strategy, ultimately, is to use data in ways that allow for faster and better decision making.  Check out how IBM StoredIQ can help you in better decision making, by taking a demo or by registering for a free trial.

2 comments on"Information Governance: A long term strategy for success"

  1. John Doe6 May 21, 2018

    It’s fascinating that organizations are using data in this way.

  2. SalsaShark42 May 31, 2018

    Is IBM going to clarify their product roadmap as it relates to things like eDiscovery? eDM and eDA haven’t been enhanced in years and they don’t integrate with StoredIQ for Legal. Atlas was shut down and hasn’t been functionally replaced.

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