Data: The World’s Most Valuable Commodity

Information is the most valuable commodity of the 21st century. At the time of this writing, the largest U.S. companies by market cap are all heavily invested in data: Apple, Microsoft, Amazon, Alphabet (parent of Google), Tesla and Facebook. Unlike other highly valued commodities, data is available in enormous (and ever-increasing) quantities from many different sources. But with so much information available, why are some companies able to utilize data to boost their competitive advantage while others lag? The answer comes down to the prevalence of data issues.

 

Information Shortcomings

“Nobody’s Perfect” and neither is your data about other companies. Here is a list of the types of informational inaccuracies that undermine your business decisions:

1. Incorrect Data

  • Causes: Misspellings, wrong information, other mistakes
  • Problem: Your employees contact the wrong customers, and everyone is confused.
  • Solution: Figure out who each company truly is. (Identity Resolution)

2. Duplicated Data

  • Causes: Unmerged accounts, one contact for multiple branches, multiple source systems
  • Problem: Your employees contact your customers once for each duplicate entry, and everyone is frustrated by the wasted time.
  • Solution: After identities are resolved, you can easily merge those that have the same identity. (Master Data)

3. Incomplete Data

  • Causes: Data is limited to only what your organization has collected through normal operations.
  • Problem: You are missing some Actionable information.
  • Solution: Find additional insights. (Data Enrichment)

4. Obsolete Data

  • Causes: Mergers, acquisitions, address changes, etc.
  • Problem: You understand who a company was, but not who the company is.
  • Solution: Keep track of company updates. (Monitoring)

 

In the simplest terms, the above issues can be remedied by:

  1. Resolving Company Identity
  2. Creating a Master Dataset
  3. Getting the Complete Picture
  4. Staying Current

Perhaps these problems and solutions seem obvious – well, we think so! Unfortunately, resolving these data issues to the standard you need is a daunting task.

Because you don’t have the time or resources to manually find, fix and add (much less monitor!) all of this information. Even if you hired a large team to focus on this exclusively, your data would still suffer from a high level of the previously discussed problems. Human error can’t be completely eradicated from the process. What then, can you do?

 

Digital Transformation with Matchbook AI

Matchbook AI has powerful, scalable tools which can help you quickly solve your data problems. We’ve used our partnerships with Third-Party Data Providers and our deep data expertise (and a lot of time and effort) to build streamlined, customizable processes. Here are the simplified steps that show how you can resolve issues for reliable data.

 

1. Resolve Company Identity

You do the following:

1. Choose and define the preferred data provider(s).
2. Choose confidence thresholds for automatic matching.
3. Provide information about companies (Name, Address, etc.)

(This can be automated in a variety of ways.)

Then we (Matchbook + Data Providers) do the following:

1. Compare your data with third-party information to produce potential matches.
2. Automatically match according to your preferences and rules.
3. We return to you:

    • Potential matches for your Review
    • Inputs without potential matches
    • For inputs that did not get automatically matched, we provide Data Stewardship tools to help match manually.

 

2. Create a Master Dataset

You can do this within your company, or we can manage your data for you.

 

3. Get the Complete Picture

You do the following:

1. Choose data enrichments.
2. Choose data provider preference and/or agreement requirements for each data enrichment.
3. Provide which records require the enrichment(s).

(Prerequisite: Identity Resolution to a Data Provider.)

Then we do the following:

1. Lookup the relevant information from the relevant data providers.
2. Return to you the desired information, according to your preferences or requirements

 

4. Stay Current

You do the following:

1. Choose which records and data points require Monitoring.
2. Choose a frequency for receiving updates.

Then we do the following:

1. Monitor for relevant updates.
2. Provide updates on your desired schedule.

 

Highest Confidence in Data

Third-Party Data Providers are in the business of providing the highest-quality data to their customers. Usability isn’t always their top priority. Matchbook AI provides seamless integration and cross-referencing to multiple providers, bringing data quality to the next level.

Maximum Flexibility

Matchbook AI gives you full control over the who, what, where, when, and how. Why? Because every organization is different, and you know your needs better than we do.

Value Recognized Quickly

Matchbook AI can positively impact your business in a matter of weeks.

Improve Employee Productivity

With Matchbook AI’ automated processes in place and high confidence in your data, your employees won’t waste time contacting the wrong people, fixing incorrect information, or attempting to piece together a puzzle manually.

Impact the Entire Organization

Matchbook AI provides Centralized Governance and Distributed Control in Identity Resolution, Enrichment and Monitoring. This means that your organization can define the appropriate level of segregating vs sharing Data Stewardship responsibilities and results.

Long-Term Maintainability

With Matchbook AI’ Monitoring in place, you will automatically receive updates, so you will stay up to date into the future.

 

Want a demonstration of how Matchbook can help you eradicate data issues? Or learn how to try Matchbook Essentials for $0/month? Get in touch with our sales team.  

 

References:

[1] https://companiesmarketcap.com/usa/largest-companies-in-the-usa-by-market-cap/
[2] https://www.economist.com/leaders/2017/05/06/the-worlds-most-valuable-resource-is-no-longer-oil-but-data
[3] https://www.statista.com/statistics/871513/worldwide-data-created/

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