Information management

Information management (IM) is the collection and management of information from one or more sources and the distribution of that information to one or more audiences. This sometimes involves those who have a stake in, or a right to that information. Management means the organization of and control over the planning, structure and organization, controlling, processing, evaluating and reporting of information activities in order to meet client objectives and to enable corporate functions in the delivery of information.

Throughout the 1970s this was largely limited to files, file maintenance, and the life cycle management of paper-based files, other media and records. With the proliferation of information technology starting in the 1970s, the job of information management took on a new light, and also began to include the field of data maintenance. No longer was information management a simple job that could be performed by almost anyone. An understanding of the technology involved, and the theory behind it became necessary. As information storage shifted to electronic means, this became more and more difficult. By the late 1990s when information was regularly disseminated across computer networks and by other electronic means, network managers, in a sense, became information managers. Those individuals found themselves tasked with increasingly complex tasks, hardware and software. With the latest tools available, information management has become a powerful resource and a large expense, as well as risk, for many organizations.

The consequences of poorly managed data can be significant. Consider the following examples:

1. Financial losses: Your organization's headquarters are flooded unexpectedly. Your backup system is outdated, and, as a result, you lose months of data, worth millions of dollars to your organization.

2. Litigation risk: Hackers access your customer database, which includes addresses and credit card numbers. These customers are now at risk of identity theft, and they decide to sue you for violation of their privacy.

3. Excess data storage costs: Your organization has no process for data cleansing – replacing or deleting inaccurate, incomplete, or outdated information. Consequently, your data storage costs and IT resource needs double each year.

4. Inefficient workflow processes: Your team members can't find the information that they need to do their work, because each department has its own database, and none of these systems communicate with one another.

5. Negative press/publicity: One of your team members loses their laptop, which contains information about a well-known client. As a result, your organization receives negative media coverage and you lose a number of clients.

Put simply, when you can't get your hands on the information you need, or when the information you have isn't protected appropriately, you can miss opportunities, your performance drops, your projects and customers suffer, and you lose competitive advantage.

If effective data and information management is important within your industry, then it should be given serious, long-term attention from everyone from the CEO and CIO down to the newest employee on the team.

Keep in mind that overhauling an existing system or syncing all of the databases in an organization can be an enormous, costly, and difficult project that can take months or years to implement – this may make it impractical, particularly if other projects will deliver a bigger business benefit.

However, you can take other steps to improve data management for your team, and for your organization.

1. Identify frustrations

Start by listing the frustrations, bottlenecks, and inefficiencies that you experience regularly with information and data availability. Next, ask your team members to describe their frustrations regarding data and information. Lack of access or inefficiencies may be affecting their work in ways that you are not aware of. Once you have a list of current issues, perform a Root Cause Analysis to trace each issue to its origin. This analysis can help you determine whether these problems, errors, or inefficiencies are the result of technical, maintenance, or human issues.

2. Review Security

The frustrations that you listed above could be a result of valid data security measures. For example, most organizations restrict access to personal information, such as employee salaries and vacation schedules, customer credit card data, or sensitive sales and financial data – clearly, you need to think carefully about who can access this information.

Start by conducting a Risk Analysis to identify any data security issues. Talk to other departments within the organization – particularly accounts, internal audit, compliance, and legal – to see if there are any issues that you need to be aware of.

3. Streamline Processes and Systems

Talk to your IT department about the problems, inefficiencies, and security points that you have identified. They might be able to fix some of these issues, or they might be able to suggest new ways to access the data that you need. At a minimum, letting IT staff members know about your frustrations gives them important feedback that they can consider during system upgrades and redesigns.

Your IT department might have a list of best practices and guidelines that you can use to streamline information, avoid duplication, protect sensitive data, and use existing systems more efficiently.

Talk to your team members about steps that they can take to improve their own data and information management. Do they have files or software that they are no longer using that can be deleted? Are they taking unnecessary risks with sensitive information? Do they keep files and folders organized, well-maintained, and up-to-date?

Think about the steps that you can take to improve data "housekeeping." Routinely going through your files and deleting old, inaccurate, or incomplete documents and programs can help reduce data storage costs for your organization; it's also a smart way to manage your electronic files. There may also be a central database that you could update, so that others in your organization can access your department's information.

4. Create Business Cases for Systems Improvements

For some organizations, data and information management may not be a high priority, and, for some, it may not seem relevant at all. If data management isn't as high a priority as it should be within your organization, you might have trouble getting buy-in for your proposed improvements.

Brainstorm the ways that improving data and information management could benefit your organization. If appropriate, write a business case outlining these ideas and proposals, and explain how your proposed systems improvements will help the organization and eliminate the consequences of poorly managed data.

According to a survey by a consulting agency Capgemini, nearly two-thirds of managers believe poor information management is hurting productivity by 29 per cent.

Nearly half of executives surveyed said a failure to deal with information lead to financial losses and increased operational costs, as well. One of the problems is the vast - and increasing - body of information now available. Some 36 per cent said the amount of data now available had doubled in the past five years, leading to respondents struggling to get a clear, singular picture.

Surprisingly, the issue isn't just technology. Nine out of ten of the top barriers to information exploitation weren't related to systems, but policies, skills and culture. Indeed, battling the issue will require improving staff training, treating information as a corporate asset, and leading information culture from the top.

A great example of a data-driven corporate culture is Google. Google is a company in which fact-based decision-making is part of the DNA and where Googlers speak the language of data as part of their culture. In Google the aim is that all decisions are based on data, analytics and scientific experimentation.

In companies data should be collected to provide answers to the most important questions and unless you are clear about the questions you need to answer, data is pretty useless.

In Google today, the aim is to start with questions and be very clear about the information needs at the outset. There are thousands of great examples of how Google applies this thinking but let’s look at a great case example from their HR department.

Within their global HR function, Google has created a People Analytics Department that supports the organisation with making HR decisions with data. One question Google wanted to have an answer to was: Do managers actually matter? This is a question Google has been wrestling with from the outset, where its founders were questioning the contribution managers make. At some point they actually got rid of all managers and made everyone an individual contributor, which didn’t really work and managers were brought back in.

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