Digital transformation is a necessary step for companies wanting to build capability and differentiate themselves from the competition.
Data debt should be considered as part of a transformation journey in order to realise benefits.
Bad, missing or non-compliant data is more than annoying – it can cost time, money and thwart strategic goals.
Imagine you’re buying a house. Instead of talking to a financial advisor or accountant, or scrutinised your bank accounts, what if you just purchased the first house that you saw?
Without question, this would be disastrous. Depending on your requirements – not only may the house not fit your needs, your bank account may not fit the house. What if your debt was so high that you couldn’t keep it, or the dwelling so small you couldn’t fit your family in?
A digital transformation can be viewed in a similar fashion. In much the same way you (hopefully) wouldn’t buy a house without considering your financial situation and its implications for your future goals, a digital transformation shouldn’t be locked-in without considering a different kind of asset – your data.
Digitising your business can be a complex process. Adding another factor to the journey is not something you likely want to hear – but data is one thing that, like your personal finances, can derail your plans and render your end state unfit for purpose.
It’s well worth putting in the time to explore your data situation upfront. If your transformation goal is to be more agile, flexible, customer-centric or automated than you are currently, then you will need data to make use of your new technology and systems. If you install new tech, but have data debt? It won’t lead to the outcomes you want, or enable some of the most useful options – such as digital twins or artificial intelligence – to work.
But what exactly do we mean when we talk about data debt? Like tech debt, it’s complicated. Without good data, you’ve likely been making decisions with an incomplete picture of where your organisation stands, not getting the results you expect, or worse, developing strategies that lead to losses. This is data debt.
Data debt can occur when companies take shortcuts or create workarounds to deal with bad data. Do different departments in your organisation have spreadsheets hoarded away with ‘their’ data? Do you have more data than you need (creating a privacy nightmare) or you have data everywhere but don’t know how to access it, if it’s complete, or up to date? You may even have great data-management software – which has been used differently by different employees resulting in patchy information. Often, data debt can be caused simply by having data on multiple platforms, none of it interconnected.
All these issues lead to a data ecosystem that is unhealthy. This causes data debt. It wastes time, costs money, undermines decisions, causes platform stability issues or outages, and can render cutting-edge technology moot.1 And if you don’t have the right data at the right time in order to deliver the right outcome, your data loses its value and your digital transformation becomes toothless.
Before starting a transformation here are some things to consider:
Define what you need – What data is critical to your success? Like buying a house, you need to think about what you’re going to be doing with it in the long-term. Know where it is coming from (customers, third parties or internal) and define what you plan on doing with it so you understand what you need (and what you don't need).
Refine your requirements – To assess whether the data you have (or that you need) is fit for purpose, you’ll need to establish quality requirements and baselines. This should include assessing your data’s reliability, its cleanliness, security and any related privacy or compliance implications.
Understand your level of debt – Not all debt is bad, but to move forward you need to understand the type of remediation required (of data or systems using/generating it) to get it up to scratch. This means the cost and effort of reducing any debt is factored into your transformation from day one.
Don’t stop – Because of its nature, data will always be accumulating in a growing digital organisation. Even if you ‘clean it up’ for a transformation, you will need to embed continuous improvement data debt cycles into your processes to ensure it stays useful. This entails a combination of people, processes, technology and a progressive data management culture.
Appoint a data leader – Someone should be in charge of your critical data in the same way your CFO is in charge of watching over your money. Linked KPIs will help ensure that your data debt is actively worked on and not forgotten. It should also be this guru’s role to advocate, educate and promote data literacy within the organisation, including the C-suite and board.
Protect your investment – Having made sure your data is fit-for-purpose for your newly transformed organisation, don’t risk slipping back into debt. Ensure that clear data governance policies and guidelines are implemented and everybody understands what is expected of them. Think about appointing data owners/stewards to maintain critical data sets and run data quality processes (such as maintaining, extracting and sharing).
Track and measure value – To maintain the value of your newly cleaned data, adopt a ‘data scorecard’. Include five to seven data metrics that matter the most to your organisation and report on them regularly. Ideally, this should be cascaded up from executive, management and operational data scorecards.
Your data is the lifeblood of your business, a critical competitive asset that is crucial to digital transformation. Ignoring data debt will not only affect your day-to-day operations, it will grow as your data volume does. Instead of a differentiator, your data might end up becoming a liability, impeding your ability to deliver a successful transformation, causing compliance or ethical concerns, or leaving you unable to exploit the next generation of technical capabilities.
Data debt is not an abstract problem. The issues we’ve seen in our work with clients are varied: customer complaints going through the roof, KPIs incorrectly calculated and performance not accurately measured, reports and analytics not reflecting reality and leading to bad acquisitions or faulty strategic decisions. Imagine if due to bad data and a new transformation, your customers stopped receiving invoices? Or past customers suddenly got correspondence from you contravening their privacy instructions? These are real issues with real dollars attached to their rectification.
On the other hand, by managing your data debt before you attempt a transformation you should end up in a place where you know what your data is, how it’s used and how it flows in your organisation, ultimately, ensuring that your data is an enabler rather than an impediment. With reduced data debt, a world of advanced technology will open up, attracting good staff, happy customers, competitors receding in the distance and, consequently, a healthy bottom line.
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