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Throughout my career, I’ve never found an organisation, large or small, that didn’t have challenges with its data. Almost by definition, applying data and analytics to business, yields issues around data quality, governance, and security, not to mention the relevance and impact of the analyses themselves. Why then, should small business be any different? In thinking about the data-related “red flags” that small businesses might encounter, while some may be universal, there are certainly others that are unique to the sector.
I’d suggest that specific data-related issues for small business fall into one of two main categories, the first which we’ll group as data management, followed by the second, which is business impact. Examples of these “red flags” are given below as well as consideration as to how they can be mitigated or avoided all together.
Data Management
Small businesses typically don’t have the luxury of dedicated teams or resources to curate, secure, and organise their data. As a result, data management can cause disproportionate problems that result in poor data quality, inconsistent maintenance, and potentially inaccurate analyses. Specific challenges include:
- Premature Data Democracy: One of the touchstones of modern data and analytics is “data democracy”, whereby data is made available directly to empowered employees, to speed up decision-making. While a tempting option for small business (due to less dependence on centralised data services), it can wreak havoc within unprepared organisations as staff take on additional responsibilities, often without training or support. Don’t assume that merely providing access to data is anywhere near enough to derive value from it – true data democracy requires a mature data culture within the organisation. Platforms such as Domo can help small businesses democratise their data for better accessibility, visibility and decision-making.
- Absence of Data Standards: It’s all too easy, within any-sized organisation, to assume that everyone knows what the data means, and how it is to be used? In practice this is rarely the case as evidenced by comprehensive standards and policies in place at larger organisations. Without the ability to classify and use data effectively small businesses run the risk of committing serious errors, or best case wasting significant amounts of time. The relatively simple task of creating (and maintaining) basic data standards should not be neglected.
- Effort Acknowledgement: Perhaps the hardest aspect of managing data lies in the acceptance that both ongoing effort and tenacity are required. Data governance is often seen as a “necessary evil”, who’s demands can be ignored after initial setup or when the organisation gets busy. Truly believing that data is a critical asset, and behaving accordingly, is a practice every-sized organisation must adopt.
Business Impact
Regardless of organisational size or complexity, once committed to a data and analytics program it is critical that it delivers tangible value to the business. Unfortunately, many businesses are awash in “vanity metrics” that fail to move the needle, or worse, analytics that are meaningless and just waste time and energy. Key red flags around business impact include:
- Low Data Literacy: One thing that can quickly derail a data and analytics effort is when people don’t understand the data they are working with. Likewise, despite frequent claims to be “data-driven”, leadership often fail to understand what the data is telling them and are unable to translate understanding to action. As a foundational skill it is imperative that all businesses instil basic data literacy skills across every role, and especially those with leadership or decision-making responsibilities.
- Unsubstantiated Use Cases: Much as in the case of vanity metrics it is very easy for an organisation to pour data and effort into use cases that, while possibly interesting, have little to do with business performance, or worst case are just wrong. Likewise, there can be a tendency to believe the value of specific data or analyses is “self-evident”. With limited budgets and resources that are typical of small business it is even more important to select and understand that use cases that make a difference and are worth pursuing.
- Poor Risk Awareness: Once an organisation starts getting its hands on some data, and begins generating insights it can be easy to lose sight of the fact that the data is not always correct, nor are your algorithms or models. Experienced teams factor these risks into their decisions and action plans, however smaller or less mature organisations may not even recognise the risks of a bad decision, let alone know how to mitigate it. The more valuable your data, the potentially higher the risks – plan and act accordingly.
As we can see there are plenty of challenges in getting the most from your data, no matter what size the organisation is. These red flags may provide insight into some common areas of concern, however the fundamentals of good judgement, knowing your business, and objective leadership will always pay benefits. Remember, your data is only there to help you make better decisions – understand that and you can’t go wrong.
For more information, visit www.domo.com. You can also follow Domo on LinkedIn, X and Facebook.
Brad Kasell is Principal Technology Strategist at Domo Asia-Pacific.
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Last Updated on October 9, 2024 by Brad Kasell
