Are You a Data Hoarder? Learn How to Manage the Clutter

Are you a data hoarder? If your data looks a bit like this, read on. Many businesses are feeling the pressures of data overload.

Are you a data hoarder? If your data looks a bit like this, read on. Many businesses are feeling the pressures of data overload.

Businesses are stockpiling more data than ever before. From machine-generated data, social sentiment, transactional data, and emails, many companies feel as if they are drowning in data. According to a report by the Economist, 7 in 10 companies are collecting syndicated third party data such as weather information (72%) or government data (70%), while many gather data such as staff data (66%) and location-based information (41%).

For many companies, this data is often siloed or is in a format that can’t be used – making strategic decision-making from so much data almost impossible. The Economist reported that 40% of executives are struggling to understand which data actually matters, while another 34% believe that their decision-making is being affected by this data overload.

Data can be one of the most powerful tools to improve customer experiences and increase customer acquisition and retention. In the report by The Economist, the top 3 areas where data has made a positive impact for CMOs are:

1. Increasing customer understanding an segmentation (50%)
2. Increasing sales (40%)
3. Helping assess potential demand for new products and services (37%)

Determining which data to use and what to toss depends on your objectives.

Here’s how to get started with transforming your data into useful information.

Perform a Business Needs Analysis

A business needs analysis should be performed to understand what is required of data moving forward. For example, what information is required to meet strategic objectives and is the data accessible to users? Are data gaps occurring, limiting the availability of required information to support decision-making? What data issues may be impacting revenue, increasing costs, or causing inefficiencies in operations?

Documenting business objectives helps determine what data should be captured, how the data is related, and how data should be structured to create value.

Dedupe and Delete

Useless and duplicate data will only provide needless information that will bog down marketing, sales, and operations. Collecting and maintaining the data can also be very expensive.

If you aren’t sure where to begin, get a data assessment. Many vendors offer complimentary assessments to help identify areas where data quality can be improved, duplicate data, and other areas where performance can be improved.

If your data isn’t already integrated, data integration and quality software automates integration processes and improves data quality by performing the following tasks:

• Parsing and standardization
• Matching and linking data
• Monitoring to ensure data continues to align with business rules
• Enrichment through data appending

Business processes should also be established to ensure data manually entered into systems is of the highest quality possible. Many organizations experience data errors when information is manually entered, at a rate of 2% and 8%.  Even one wrong number entered incorrectly can cause a payment to fail, a wrong part number to be shipped, or apparently a man to become pregnant.

Data validation controls can be integrated into on-line forms, using rules to check the validity of data sets. For example, an on-line website form may require a visitor to enter data in specified formats. Or an IRS form may utilize controls to check that positive numbers are being entered into fields.  Training employees to be more aware of the importance of data quality is also a crucial step to achieve a company-wide awareness of maintaining high quality information.

Appoint a “Keeper of the Data”

Once a system has been put in place to flush out the bad data, you don’t want to fall bad into bad data hoarding habits so be sure to appoint a “keeper of the data”.  You don’t need to rush out and hire a data scientist, but someone within the organization should be responsible for the data, such as a data steward who understands what to do with all the data that is being collected. Responsibilities of this role should include:

• Identifying and acquiring new data sources.
• Defining business rules on how data will be maintained and used.
• Maintaining the quality of data and resolving any issues.
• Specifying data retention requirements.
• Ensuring business users adhere to specified data standards and rules.
• Determining data security requirements.

When it comes to information, too much can hurt. Take action to manage the clutter and concentrate on the insights that matter.