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Steps to Efficient Information Lifecycle Management

Steps to Efficient Information Lifecycle Management

Information Lifecycle Management is imperative to businesses that are data-dependent. In fact, all businesses are fast-evolving to be data-intensive. Data helps them to understand the market requirements and competition which makes them more competitive.

But handling large volumes of data is a meticulous process and hence the need for ILM is as important. There are many approaches to managing the information lifecycle. Here are some of the important steps in efficient Information Lifecycle Management. Before you start implementing the ILM process, you need to consider these:

Ensure Regulatory Compliance

Every country and state will set a statutory documentation compliance for every
business. Before you can set the ILM strategy, you need to understand the
regulatory requirements. What all documents are required, how long you need to
maintain them, and in what format the documents need to maintained etc are to
be determined first.

Check Storage Efficiency

Businesses sometimes tend to store all types of information in a single storage
device. This is not the right way to store data optimally. Storing relevant and
irrelevant data in the same device will adversely affect the efficiency of the
storage system. Instead, data should be segregated based on its relevance and
frequency of usage.

Define the data requirements

What kind of data is required for your business in the short and long terms? This
is a critical question to consider while devising the ILM strategy. The business
goals and rules will help to determine the data requirements.

Determine the lifecycle

For each piece of information, you need to determine its importance, the phases
it will pass through and how long it should remain in the system. This will
determine its lifecycle.

Identify the business value

Every piece of information should have some business value to be included in
the ILM. To determine the business value, you have to identify its need, use, and
keywords. Based on this, its business value can be determined.

Automate data migration

Finally, the data migration rules must be set and automated. It is important to
automate the data migration rules for smooth transition of information from one
phase to another. Automation makes ILM more efficient and effective.

Once these basics are managed, the ILM strategy can be well-devised. Here are
the steps.

1. Identify the Data Growth Trends

The rate at which the business grows determines the rate at which its data grows.
The data growth rate has to be determined to identify the volume of your
business data that will be generated and that has to be dealt with. Data volume
is an important aspect that determines your data storage and archiving
requirements.

2. Set the Success Principles

Data should align with your business principles. Set your business goals and
make sure that only such data that align with those goals will need to go through
the different phases of ILM.

3. Establish Policies

Data policies, especially the retention policy, should be well established. What
data should be retained for how long should be well-defined. This will determine
when it should be discarded or archived.

4. Mind the Business Rules & Test them

Business rules are set to make sure that data conforms to their requirements.
Your data processing tools should make sure that the business rules are met and
the data is complete and accurate. This should be tested using automated and
manual techniques. Data that does not conform to your business rules must be
corrected or discarded immediately to reduce the processing overhead and
increase the process efficiency.

5. Set User Access policies

User access policies should be set and managed in a secured way to make sure
that data privacy is maintained. Only authorized users or user groups should be
given access to chunks of data that’s classified. This will make sure that data is
secured.

6. Ensure Data Restoration

Important data should be archived and be available to restore when required.
Data subsets are used to locate the archived data quickly. This makes the data
storage and archival more efficient since data that’s not immediately required
can be archived and moved to a different server while the current and active
data can remain in the main data server. Automatic migration can be set for
archiving and shifting data based on pre-set business rules and policies.

7. Follow proven methods

Proven methods make sure that ILM is not disruptive. In an ongoing organization,
information transition has to be smooth. This is assured by proven
methodologies and tools. A new or experimental method may result in process
disruption which will jeopardize the business in a large scale. Since most of the
businesses are dealing with bulk data on a daily basis, even a few hour’s
disruption will cost the business significantly. It is hence important to choose
proven methods for ILM.

Information Management Li7. Follow proven methodsfecycle implementation will be different for different
businesses. It depends upon how the business uses the information and the
volume of information it has to manage. Telecom businesses may discard
discontinued users’ data after a few years while banks must maintain the
information much longer. The business value of information also plays an
important part in determining its phases and accordingly the ILM strategy is
formed. In governance, information is very sensitive and hence, user access and
security should be well-defined. Data quality, business rules and goals, archiving
and accessibility, all have to be carefully defined in the ILM implementation
strategy. Since the ongoing businesses cannot afford to compromise on data
quality and process disruption, a tried and tested methodology is advised.
Carefully analyze your data, requirements, processes, and goals to implement
Information Lifecycle Management for your business.

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