Data helps a company do a number of things:

• Understand better who your customers are and what they are buying – Who are your customers? Baby Boomers? Gen Zers? Gen Xers? Data helps you analyze what you are selling to who, where and how? How can you serve them better?

• How are you doing Vs your competition– How satisfied are your customers? How are your competitors faring compared to you? What are quantitative metrics that help you determine this? What are some qualitative metrics such as Net Promoter Scores for you and your products?

• How are you doing operationally? – What are your manufacturing and distribution data telling you about your Operational Efficiencies and Effectiveness?

Many organizations are realizing that they have petabytes of data collected already and data volumes increasing by orders of magnitude every year!  Reality is that the data organizations are collecting are so sensitive that they fear sharing them even internally! Here are some examples that prevent organizations from using this data and deriving the myriad insights they need as above:

• Personally Identifiable Information (PII) – So much of the data organizations collect have Customer and Employee information that are deemed Personally Identifiable Information (PII) – like names, addresses, social security numbers, etc.  These have to shared even within the organization selectively since breaches can be financially catastrophic for any organization. 

• Personal Health Information (PHI) – Many organizations deal with information about employees such as Health Insurance, mental health issues, etc. that are deemed Personal Health Information (PHI). These are also shared very selectively within the organization for fear of breaches and their financial consequences.
• ‍Sensitive Customer, Product, Sales, Intellectual Property Information – Customer Bank Account, Credit Card information of customers, product manufacturing and sales data, Intellectual Property Information are all data to be guarded and shared even within an organization very selectively and with a lot of safeguards.

So, in theory, an organization has a lot of data. But, sharing of this data within that organization is hampered severely by the above concerns. Converting your real data into synthetic data liberates all this data for internal use bypassing many of the sensitivity concerns above. Privacy Assurance algorithms and reports, when run on synthetic data that is generated, can ensure that no PII or PHI or other sensitive data is shared even internally within an organization.

Value of data can finally be unlocked for use without worrying about breaches. Product, Sales, Customer segmentation analyses can all be performed just as easily with Synthetic Data as with Real Data if they have the same characteristics!  Financial, Marketing, Manufacturing, Sales and Operations people can all get the data they need to do a better job without worrying about whether they are handling sensitive data and who is allowed to see what. Synthetic Data can alleviate a number of concerns with more widespread use of the data that an organization collects and allows it to use them for improving efficiencies and effectiveness!

“Without big data analytics, companies are blind and deaf, wandering out onto the web like deer on a freeway.” ~ Geoffrey Moore