How Data Lineage Moves You from Red to Black

Data Lineage is the process that brings visibility, efficiency and increased profits

The way you allocate your tech investments makes a lasting impact on your organization’s future. It’s important to tread your path through digital transformation with great caution and be mindful of the unassuming processes that can make a big difference.

 

The limitations of digital transformation

The push for digital transformation has vastly increased in the post-covid world, but efforts to modernise are not always as easy as they seem. In the last five years, it has been frequently observed that most digital transformations fail, with research suggesting that at least 70 percent of initiatives will not meet their objectives. Businesses that take on a digital transformation are beset by challenges, which have various manifestations.

Difficulties experienced may be in the form of employee pushback where employees are left feeling unengaged or disempowered. Digital transformations can also be made less effective by unsynchronised deployments, undefined objectives, or a limited budget. While they attempt to break down organisational silos, in some cases, this is insurmountable.

The foundation of a successful digital transformation often lies in the ability to harness data.

While data sits squarely at the core of digital transformation, processes to manage, store, transfer, document, govern and utilize data for such transformative work have become increasingly complex and cumbersome. Instead of enabling agility within the enterprise with data-driven insights, these clunky processes instead start to hinder, corrupts data quality, and increases overall operational costs.

 

Data governance for compliance

Data governance is particularly important in the financial services sector, due to the regulatory frameworks that dictate business practices where personal data and finances are concerned. Data lineage is a key component in data governance, and it involves the tracking of data from its origin over time and the adjustments that are made.

In the past, such best data practices were merely a practical approach for increasing efficiency and avoiding errors across the organisation. But increased regulations that are strictly enforced have made this compulsory. Changes in regulatory controls have chiefly driven new processes in data management like data lineage.

Compliance risk is a growing concern in financial services, and regulatory fees have been on the rise since the financial crisis of 2008, along with new concepts like Anti-Money Laundering (AML), which threaten increasing penalties to enterprises.

As well as staying compliant with new frameworks like GDPR, CCPA, MiFiD II, there is a greater requirement for data-driven reporting in new enterprises like fintech banks and insurers. This means that keeping up with CCAR MRAs, BCBS 239 and GDPR for banks, and Solvency II and IFRS 17 for insurers is absolutely necessary.

In the face of multiple regulations, the data quality and transparency that data lineage makes possible can be hugely beneficial to financial services and institutions. Yet, in a recent survey, only 13 percent of firms were found to have complete data lineage deployments.

Data governance as a sound investment

A solid data framework with good governance is effective in meeting compliance and achieving improved operational efficiency and higher quality data. Most enterprises depend on investors that prefer to see risk kept at an absolute minimum and a level of competency that inspires confidence.

The pandemic has led to a reliance on data insights, and it has called for increased investment in data governance, architecture, and consumption. This can amount to up to a third of IT expenditure.

Investing in data lineage helps businesses to improve data intelligence and increase overall productivity. It also substantially reduces data management costs, increases data quality, aids decision-making processes, and improves customer satisfaction and reputation management. It can be challenging to quantify the value of data management, but many firms have massively reduced costs in their data ecosystem through effective data governance strategies. In one case study, a bank recorded savings from $1,480,280 to $304,140 due to a data lineage solution.

 

Data lineage not receiving deserved attention

Data lineage improves data management, data quality, and the probability of meeting various reporting requirements. It can also be used for debugging, and data incident root cause analysis. But one of the limitations of data lineage is its typical perception among business leaders. Many find that practices in data governance are not interesting but more of an unenjoyable chore that needs to get done, which means much-needed solutions are often overlooked.

David Krikheli, an Ascention “CLEAN Data Expert”, also shared in a whitepaper on the importance of culture to link data analytics capabilities to actual business practices. It is often the staff’s behaviors and values that manifest the data monetization vision in the form of imminent benefits.

Data lineage does not always appeal to people in the same way that data analytics does, yet it is a crucial process that can reduce or eliminate inefficient processes. Having a clear data lineage can prevent enterprises from becoming part of the statistics:

  • A survey published in Harvard Business Review found that as little as 3 percent of business enterprise data reached even a basic standard of quality.
  • On average, 47 percent of newly created data records have at least one critical (e.g., work-impacting) error. A full quarter of the scores in our sample are below 30 percent, and half are below 57 percent.
  • Poor data quality destroys business value. Gartner research found that organisations believe poor data quality is accountable for an average of $15 million per year in losses.
  • New York Times wrote that data scientists spend up to 80 percent of their time mired in mundane work such as “data wrangling,” “data munging,” and “data janitor work.”

These challenges can be addressed by improving data intelligence through a data lineage implementation. While it may not be the most exciting field of data management, understanding more about data through data lineage will enable businesses to avoid the pitfalls of risk in non-compliance, reap the actual business benefits of data intelligence, and cut out the waste in both human and technical resources.

 

The best investment for a firm foundation

McKinsey found through client work that by increasing focus in data management on visibility, standardisation, and oversight in five areas, businesses can recover up to 35 percent of their data expenditure. The company estimates that investment in data governance will result in 15–20 percent savings in the short term.

As a key contributing factor to good data governance through the transparency and data quality it provides, spending on data lineage will lead to immediate returns on investment. But in addition to this, this essential approach to data management will also improve an organisation’s operating costs and scalability, and in doing so, convert spending straight into profit.

With data quality as an essential attribute in the data-oriented environment, deploying an effective data lineage solution is the best investment for the forward-thinking business leader. Think your data can account for 20 percent of your business earnings this year with better data lineage? Ascention can get you there.

 

Ascention Shares Experience

Ascention wishes to impart skills and knowledge. The team at Ascention is always willing to share our experiences to assist your team’s progress – simply contact us to start an informal, no-obligation discussion.

 

Ascention Contact:

Dan Cox, Chief Executive Officer

E: dan.cox@ascention.com

M: +61 415 612 906

Ascention Data As A Language series

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