By Susan Rebner, CEO of Cyleron
Many organizations understand the importance of data but remain uncertain as to how to fully unlock its potential benefits. While organizations will often readily admit to having data strategy listed as a top agenda item, I’ve found that many fall short in terms of actually implementing a smart data ecosystem that can be leveraged as a true competitive differentiator in the digital world.
In the modern era, properly managed and curated data can yield enormous benefits. The converse, of course, is also true -- poorly managed data can lead to reputation damage, cyber vulnerability, significant competitive disadvantage and, eventually, brand obsolescence.
As companies look to develop and implement a smart data strategy, there are many obstacles that must be addressed both from a functional and technical perspective. Poor data-quality, insufficient data security, inadequate data architecture, lack of executive sponsorship and many other factors can prevent companies from achieving their objectives, as I’ve seen in my work in the cybersecurity software and solutions industry.
So, how can you achieve a data smart strategy to avoid these challenges?
Develop and document your data strategy.
The first step toward preventing and/or overcoming these obstacles is to develop and document a clear enterprise data strategy that defines the overarching vision and specifically aligns it with your business goals. The next step is to craft a clear and concise listing of quantifiable milestones to achieve it both in terms of program management, data architecture efficacy and business usage and benefit.
Many companies that are serious about using data as a competitive advantage have created positions such as a Chief Data Officer (CDO) to oversee data strategy, transformation and governance. The CDO should understand, at least at a summary level, the metadata, master data, overarching enterprise data architecture, integrations, nomenclature, etc., of the entire organization -- down to the very last datastore.
Create specific use cases.
Becoming a data smart organization is a journey rather than a destination. Moreover, it should be viewed as a marathon versus a sprint simply due to the fact that nothing is as easy as it seems when it comes to data. Upon gaining executive sponsorship and developing your data smart strategy, the next step is to create specific use cases that equate to true business value.
Begin by breaking down your strategy into its main goals and then pull out the individual use cases that are likely to produce the greatest return on investment. Take into consideration the preservation of data, data architecture, ownership and governance of data, data lifecycle, safeguards/protections and risk.
Consider your data culture.
The need may arise to vastly transform the way in which things are currently being done in order to support the realization of the newly-minted enterprise data strategy and governance framework. Both the cultural and technical aspects of how organizations interact with data are critical when developing data practices.
It is of paramount importance to comprehensively and completely document the current state in terms of how the organization defines, acquires, stores, enriches, manipulates, disseminates and uses its data in order to obtain a true understanding of its current data culture. I’ve found that many companies maintain precious little insight into the who, what, where, when, why and how when it comes to their data assets and supporting processes and procedures.
Safeguard your data.
Data governance is by no means a new concept; however, the importance has never been greater than it is today given the data deluge and internet of things. Having a robust data governance plan in place is critical to improving data quality, which directly impacts decision making, product development, customer service, marketing effectiveness, enterprise value, etc.
A common misconception is that data quality issues are largely due to technological misalignments. The reality, however, is that insufficient data quality is often linked to human error or lack of concrete data definitions.
It is also crucial to significantly elevate the organization’s cyber defense posture by implementing privacy-focused constraints and minimum access right mechanisms at the lowest possible levels within the technology and policy footprints. Safeguarding data requires anticipation and mitigation planning of the company’s data, as well as a relentless focus on cybersecurity preparedness and responsiveness.
Without question, organizations can transform themselves from being ad-hoc data focused into smart-data oriented, best-in-class information entities with the appropriate commitment and follow-through. The fact of the matter is that every company should view itself as an information company whereby the difference between thriving and going out of business largely comes down to a bunch of ones and zeros.
Susan Rebner is the CEO of Cyleron, an artificial intelligence enabled cybersecurity software and solutions company.