In this guest editorial post, Dr. Ansar Kassim, Head of Financial Analytics at Verizon and recent winner of the 2022 Analytics Leader of the Year at Corinium’s Business of Data Awards Gala asks: How do you know if your data is an asset or a liability?
Unsurprisingly, most business leaders think of their data as an asset. ‘Data-backed decision-making’ is something we all hear and talk about, myself included. How, then, could data be anything but an asset if it supports business decisions? In my view, the answer is: If your data is working for you, it’s an asset, but if you are working for your data, it’s a liability. So this is not a discussion about data security, which technology leaders often associate with liabilities arising from data.
Leading indicators your data is a liability
If you have a team responsible for gathering data from disparate systems, cleaning and fixing any issues with it, then analyzing and creating tens to hundreds of reports for different stakeholders and functions within the organization, over and over again—that’s you working for data. On the other hand, if you have technology that automatically collects, cleans, and analyzes the data so that people can preserve their time for extracting value and insights out of it to ultimately inform decisions and shape strategies—this is data working for you.
Unfortunately, leaders and their teams can easily get caught up working for their data because of the age-old concept of the ‘rat race’. A book I admire by Robert T. Kiyosaki and Sharon Lechter, called Rich Dad Poor Dad, describes the ‘rat race’ as a vicious cycle learned early in life that tells us the only way to get ahead in school, in our careers, and in life generally is to work harder and try harder than everyone else. It’s a cycle that’s hard to break because we get lost in it too easily and overcome by the day-to-day hustle, not realizing there’s another way.
But there is another way. Leaders need to pause, take a step back, and ask themselves if any of these leading indicators ring true for their organization. If the answer is ‘yes’ to any of these, your data is likely a liability:
- Is your team working mind-numbing, long hours, solely focused on gathering, analyzing, and reporting out data?
- Are you and your team busy churning out an exorbitant number of reports or dashboards and busy fixing issues with those reports?
- Are you still receiving a high volume of customer complaints about your products, solutions, or services?
- Are your internal stakeholders complaining that they’re still not getting the insights they need from reports?
- Are your stakeholders going to your team rather than to systems to answer their questions?
This last question alone is incredibly important in understanding the nuances of data. If data is truly an asset, teams or individuals within your organization can rely on shared data and insights to answer their questions, or even gather it themselves. If it’s a liability, however, those same teams and individuals will come back to the people who shared it with their questions, with no real weight lifted off those working with the data.
How to turn your data into an asset
When it comes to data, we need to do better. But what exactly is a data asset? Typically, in the form of databases and dashboards, it’s anything that enables teams to better understand key operational elements that add value, increase competitiveness, and directly impact revenue, such as usage, utilization, and inventory.
It’s time for business leaders to break free from the ‘rat race’ and shift their data from being a liability to serving as an asset. This is how they can get started:
Understand the asset-to-liabilities ratio: Every organization has both data assets and data liabilities, but what is important is to have more assets than liabilities. In other words, your asset-to-liability ratio needs to be more than one. A good ratio will allow the organization to generate a positive ROI from data that will allow returns from the asset to be reinvested to form a positive spiral. However, if the ratio is less than one, you will end up throwing more resources at the data team to maintain the same level of returns.
Realize that today’s asset may be tomorrow’s liability: The asset-to-liability ratio is dynamic. Assets, for example, can depreciate over time if they’re not properly managed and maintained or if their capabilities are not well understood or fully leveraged from the beginning. Say an organization implements a new platform to streamline data analysis for one team, but it disrupts another team’s processes that relied on certain functionalities of the previous system—that asset ultimately becomes a liability because it now requires more attention, or even more systems, to keep everything running smoothly for everyone.
Do not add more liabilities in the process of building data assets: Investing in more systems is typically the first move when organizations realize there’s a data problem. This is certainly one way to approach it, but like the example above, if it happens too quickly or without thoughtful consideration, it often results in organizations adding on yet another liability. How, if you don’t understand the core of the problem first, can you truly fix it? While a new system or platform may solve your issues, what if it creates upstream or downstream challenges for a different team? Throwing money at the problem isn’t a solution in itself. Leaders need to diligently assess the foundational data challenges they’re experiencing first, come together as a team to solve them, then invest in the right systems to help. Otherwise, they’ll be doing the same exercise all over again in a few years when they realize they’ve adopted another liability.
Develop an asset monetization strategy: Even if you build a true asset, you need to have a clear monetization strategy. What is the advantage of acquiring a rental property, if there is no marketing strategy to monetize the asset? Often executives make the same mistake of trying the same old formulae that ended up failing several times in the same organization. Another common mistake is to borrow a strategy that succeeded in another firm. Your firm has a unique cultural fingerprint, and you need to find what works in your firm’s cultural context. If you are unable to get bottom-up adoption, try top-down adoption. Test micro-experiments that allow you to identify a workable and scalable data asset monetization strategy.
Convert your key data talent into data asset generators: Importantly, one person shouldn’t be responsible for answering all data questions or solving all data problems. Every organization has rock stars who can find answers to every data question. Treat those rock stars as true assets who are capable of creating more assets. Instead, if they are answering questions, you will see them evolving as bottlenecks. While bottlenecks are not liabilities, they will be too preoccupied to sustain operations, which can otherwise be used to build data assets. Rather, teams need to be empowered with self-service solutions because, when people can consult systems rather than other people, it removes friction, reduces hesitation, and creates a team of confident decision-makers.
Eliminate your liabilities (burn the boats): This is often the most challenging step. This is the “burn the boats” step in data culture transformation. Once you have built an asset with an adoption (monetization) strategy that is working, you need to start eliminating the liabilities that got you there. If you retain your liabilities, you will have to keep paying for them. More importantly, there will be residual adoption for your liabilities, and if you do not eliminate them at the right time, the residual adoption will be the biggest hurdle that prevents you from eliminating the liability. If you don’t eliminate the liability, it will become that much harder for you to build an asset-to-liability ratio that is greater than one.
If organizations continue to carry on working for their data, their workforce and their business partners and customers will eventually take notice. And when they do, they’ll leave and find a company whose data is truly an asset. That’s how powerful data really is—it can hold back or bring down an organization if it’s a liability, but alternatively, it can propel a business forward when it serves as an asset.
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