how much data do you have and how good is it?
According to a recent Harvard Business Review article, only 3% of companies' data meet basic data quality standards.
Chances are, if you are reading this, you are in the 97% of companies who do not.
We've spent over 25 years working with companies to help them assess and remedy their data quality issues. From creating a data inventory to assessing and fixing your data quality issues, we have the experience and tools needed to help you unlock the value that exists within the vast pools of data that reside within your organization. Take a look at our services below and contact us today to learn more about how we can help you.
Chances are, if you are reading this, you are in the 97% of companies who do not.
We've spent over 25 years working with companies to help them assess and remedy their data quality issues. From creating a data inventory to assessing and fixing your data quality issues, we have the experience and tools needed to help you unlock the value that exists within the vast pools of data that reside within your organization. Take a look at our services below and contact us today to learn more about how we can help you.
Data Inventory
Know what exists
It would be ludicrous to consider purchasing the physical assets of a company without having some form of inventory of those assets. Especially if those assets were to form the basis for future growth. Effective use of data has shown to be a driver of performance, yet few companies create or maintain a proper data inventory. The reasons vary, but for the acquirer it is absolutely critical to have an understanding of what data the target has in its possession for a variety of reasons:
It would be ludicrous to consider purchasing the physical assets of a company without having some form of inventory of those assets. Especially if those assets were to form the basis for future growth. Effective use of data has shown to be a driver of performance, yet few companies create or maintain a proper data inventory. The reasons vary, but for the acquirer it is absolutely critical to have an understanding of what data the target has in its possession for a variety of reasons:
- If the post-acquisition strategy involves either organic growth or improved operational efficiencies, having a solid understanding of the data available to power that strategy is critical.
- It may be necessary to purchase additional data sets to power that strategy but how would you know how much this would cost or understand the effort involved if you didn’t already know what you had?
- From a risk perspective it is important to know if there are any toxic assets that would require enhanced security measures or remediation.
Data Quality
How good is it?
Would you buy a used car without at least taking it for a test drive? Of course not. Because regardless of your knowledge of automobiles, you would want to have some sense of the quality of the car you are considering buying. The same holds true for data. Just because its stored in a database doesn’t mean that its of good quality. There can be a massive amount of duplicates, missing values, and inconsistencies. In fact, 97% of companies don’t have quality data. Poor quality data causes significant downstream impacts through waste, inefficiency, and lower productivity. In fact, some studies have shown that 50% of office based staff’s time is wasted dealing with data quality issues. Data scientists often spend 80% of their time cleaning data before they can even begin building analytics.
Our proprietary tools and methodologies will assess and analyze the data quality of a target company’s information assets. This will enable you to have a solid understanding of what you are buying before you make an investment decision. This report can be used to create a more informed valuation as well as influence long term returns expectations. Should a target have poor quality information, it could take a longer and require more investment in order to cleanse it and unlock its potential. In some cases, the data quality may be poor and the level of remedial investment so high that it might make sense passing on the opportunity to avoid missing targets and impacting the funds’ overall return.
Would you buy a used car without at least taking it for a test drive? Of course not. Because regardless of your knowledge of automobiles, you would want to have some sense of the quality of the car you are considering buying. The same holds true for data. Just because its stored in a database doesn’t mean that its of good quality. There can be a massive amount of duplicates, missing values, and inconsistencies. In fact, 97% of companies don’t have quality data. Poor quality data causes significant downstream impacts through waste, inefficiency, and lower productivity. In fact, some studies have shown that 50% of office based staff’s time is wasted dealing with data quality issues. Data scientists often spend 80% of their time cleaning data before they can even begin building analytics.
Our proprietary tools and methodologies will assess and analyze the data quality of a target company’s information assets. This will enable you to have a solid understanding of what you are buying before you make an investment decision. This report can be used to create a more informed valuation as well as influence long term returns expectations. Should a target have poor quality information, it could take a longer and require more investment in order to cleanse it and unlock its potential. In some cases, the data quality may be poor and the level of remedial investment so high that it might make sense passing on the opportunity to avoid missing targets and impacting the funds’ overall return.
Data Volumes
How much is there?
How much data does the target actually have? Many firms talk about Big Data but the reality is that most firms don’t have a Big Data problem. What they have is a data management problem because they are unable to effectively manage, store, and disseminate the data that they do have. Understanding data volumes is critical for two reasons and are specifically related to the analytics strategy. In order for an algorithm to be developed, it requires a large volume of test data so that it can be refined for accuracy. However, once that algorithm has been developed it requires a steady stream of high quality data delivered in the format that it is expecting in order to function and deliver the expected results. It’s not sufficient to have just the initial pool of static historical data in order to power an ongoing analytics strategy. Of course, data volumes are also a key factor in developing a data architecture strategy but with the continuing fall in data storage costs and the increasing capabilities of cloud based storage providers, this becomes less of an issue over time.
How much data does the target actually have? Many firms talk about Big Data but the reality is that most firms don’t have a Big Data problem. What they have is a data management problem because they are unable to effectively manage, store, and disseminate the data that they do have. Understanding data volumes is critical for two reasons and are specifically related to the analytics strategy. In order for an algorithm to be developed, it requires a large volume of test data so that it can be refined for accuracy. However, once that algorithm has been developed it requires a steady stream of high quality data delivered in the format that it is expecting in order to function and deliver the expected results. It’s not sufficient to have just the initial pool of static historical data in order to power an ongoing analytics strategy. Of course, data volumes are also a key factor in developing a data architecture strategy but with the continuing fall in data storage costs and the increasing capabilities of cloud based storage providers, this becomes less of an issue over time.
Data Security
Is it protected?
It seems that every day there is another news report of a data breach at a corporation. By its very nature, data is a highly fluid asset and is also very valuable making it a particularly attractive target. Even the largest and most advanced data-centric firms struggle with keeping their data secure.
When acquiring a firm it’s important to understand the level of security risk its data presents and having a solid understanding of what security measures are already in place and would be needed on an ongoing basis. In addition, with the adoption of GDPR, nearly every firm must be compliant with its stringent regulations. Our tested processes will assess the existing security policies and procedures that are already in place and identify any gaps or failures. In addition, we can identify what tools or future actions need to be taken to ensure that the proper level of security and compliance are met.
The news only reports data security failures and these can be catastrophic for the firms involved. Isn’t it worth making sure that your new acquisition isn’t today's headline?
It seems that every day there is another news report of a data breach at a corporation. By its very nature, data is a highly fluid asset and is also very valuable making it a particularly attractive target. Even the largest and most advanced data-centric firms struggle with keeping their data secure.
When acquiring a firm it’s important to understand the level of security risk its data presents and having a solid understanding of what security measures are already in place and would be needed on an ongoing basis. In addition, with the adoption of GDPR, nearly every firm must be compliant with its stringent regulations. Our tested processes will assess the existing security policies and procedures that are already in place and identify any gaps or failures. In addition, we can identify what tools or future actions need to be taken to ensure that the proper level of security and compliance are met.
The news only reports data security failures and these can be catastrophic for the firms involved. Isn’t it worth making sure that your new acquisition isn’t today's headline?
Data Gathering
How is it created?
If data will fuel growth, isn’t it worth knowing where the data is coming from? How good are the systems that are capturing and creating the data that the organization stores. The old adage of garbage in, garbage out is particularly true for data. Addressing data issues at the point of capture is dramatically cheaper and easier to address than dealing with it once it has been stored and disseminated to downstream systems. A data and analytics strategy can be invaluable in this instance in order to ensure that the correct data is being captured in the correct format as early in the data supply chain as possible.
We can conduct a data lineage exercise on key performance indicators to ensure that the correct data is captured properly at the source and that its quality is maintained throughout the data lifecycle.
If data will fuel growth, isn’t it worth knowing where the data is coming from? How good are the systems that are capturing and creating the data that the organization stores. The old adage of garbage in, garbage out is particularly true for data. Addressing data issues at the point of capture is dramatically cheaper and easier to address than dealing with it once it has been stored and disseminated to downstream systems. A data and analytics strategy can be invaluable in this instance in order to ensure that the correct data is being captured in the correct format as early in the data supply chain as possible.
We can conduct a data lineage exercise on key performance indicators to ensure that the correct data is captured properly at the source and that its quality is maintained throughout the data lifecycle.