Surviving and Thriving Today's Perils of Data Evolution

Surviving and Thriving Today's Perils of Data Evolution

Divya Joshi, Head of partnerships, Thoughtworks & Alison Gerlach, Managing Partner, Breakthrough Ventures, 0

The job of a CEO is to optimally lead their venture to achieve potentially significant long term value. The ‘sexy’ fiduciary metrics such as revenue growth, increasing share price, and optimal profitability are often markers of whether or not the CEO and the venture are successful. However, few things bring down a venture faster than basic, ‘un-sexy’ but key issues around good old fashioned corporate hygiene and governance. Data collection, data management, and data cleanliness have been paramount to every company in every field in every market.

Over the past 20 years, there has been a fundamental shift in the social-technological construct. The faster our ability to gather data, so has the vulnerability of the data. As we’ve developed technologies to scale data collection and usage, we’ve invited complexities and security of the data we’ve come to depend on for critical insight. Today, companies battle expensive problems surrounding data leading to:

● Data insecurity – vulnerability to cyber-security issues.

● Data dependency from outside sources that may not be compatible with your own.

● Data system illiteracy -- costly training of personnel and lengthy ‘hand-off’ times.

● Data transparency and cleanliness.

All of these issues lead to ‘data fear.’ Fear of security. Fear of needing to depend on the work product from a particular expert. These issues inevitably thwart the very value that data driven KPIs have in building long term value. Effective solutions must alleviate fear in a simple yet holistic way. Successful data solutions will seamlessly and securely transfer and analyze data across multiple business units, and can be broadly accessed and interpreted by a wide variety of people inside of a company.
Many corporations spend millions of dollars on ineffective tools. The result is a severe, reverberating price. These costs can be in the hundreds of millions of dollars in fees, lost revenue, and irrevocable detriment to brand equity.

● In 2019 Google was forced to pay a fine of £44m million to the EU.

● In 2018 Uber spent $148 million to settle a data breach affecting 57 million customers.

● Marriott International paid $124M in 2019 for data related non-compliance.

Losses don’t end with fines and fixes. Dollars gone due to diminished customer confidence, investment to re-establish damaged brand equity, and opportunity cost of customers lost to a competitor can quickly run into the hundreds of millions and persist for years. A recent study of companies trading on the NASDAQ found that the share price of the companies with a data breach was an average of 13 percent lower than the Index three years after the incident.

While many have paid a severe price for their data management failures, there are some who have succeeded in navigating the complexities of data evolution. Saxo Bank is a sterling example. They adopted ‘data mesh’ and are able to maintain self-serve data
domains with a miniscule data team while being compliant to GDPR via federated data governance. The data management implementation took less than a year at a minimal cost while providing a competitive advantage in whitelisting Saxo in the banking ecosystem.

Data mesh is not a tool or a software platform that can be bought off the shelf. It is a socio-technical process, approach, and construct that decentralizes data to more elegantly manage the increasing data complexities in today’s corporations. The key tenets of data mesh are:

● Decentralization of data products and maintenance (domain driven thinking).

● Centralization of data ground rules, lineage, and controls (ownership).

● Compliance to federated data governance.

● Independence from specialized tech resources- application of product thinking (data as a

The successful leaders of today and tomorrow’s ventures will embrace solutions that expand data access, empower their employees and customers

The key outcomes of data mesh leading to higher company value are:

● Data consistency, transparency, and trust.

● Data governance compliance.

● Seamless data access and analysis to business leaders without dependence on tech folks.

● Actionable data insights.

● Security from mis-use and outside access.

So how can you ensure your venture is ‘data ready’ to protect itself from the perils created by poor data management? First, is your organization ready to embark on the data mesh journey?

1. Do you have a companywide, consumer focused integrated data strategy?

2. Do you have organizational processes and support to align incentives throughout the organization?

3. Do you have the right KPI and incentives?

Once you’ve established data mesh ‘readiness,’ there are key, executive level steps to create and
implement an optimal plan for processes and management around data and its usage in building value in your venture:

1. Assess and articulate:
. Data needs across all company functions.
. Current company data management and analysis tools.
. Data shortcomings, fears, and vulnerabilities.

2. Empower the people and customers in your organization
While no one is generally compelled to indulge in the ‘un-sexy’ discussion around data hygiene accessibility and security, it is critical that companies protect themselves from the painful bite the harsh teeth of data realities can inflict. The successful leaders of today and tomorrow’s ventures will embrace solutions that expand data access, empower their employees and customers. This will be the key that builds value in their ventures.