Data insights hold the key to making better and more profitable business decisions.
Tuning into data signals to drive better business performance
Start with your business question in mind
Tech is important, but people matter even more
Keep ethics and regulations in mind
A driver for successful business in the digital age
1. Data offers signals that can take the form of actionable insights into an enterprise’s people, operations, customers, markets, finances and assets.
2. Equipped with the right insights, an organisation can make better decisions and grow its bottom line.
3. Couple the data strategy to tangible business metrics from the outset.
4. Decide which data will help answer key strategic business questions.
5. Don’t only focus on what data is available, look at how trustworthy and relevant the data is.
6. For data to be transformed into an actionable insight, it should provide a credible explanation for a trend or action, as well as offer guidance about what to do to get the best outcome.
7. Start moving away from data siloes and move towards democratisation of data.
8. Instil a culture of data-driven decision-making, where insights are used to empower people and foster collaboration.
9. Use data in a responsible manner and build a data ethics framework from the outset.
10. SMBs need access to insights that help them sharpen their competitive edge, optimise their businesses, and drive profitability during difficult times.
‘Do more with less’ is the mantra of the owner or leader of nearly any small and medium (SMB) business in Southern Africa. In the wake of the pandemic and the grips of a tight economy, the SMBs that are smartest about capitalising on their opportunities, stretching their resources and adapting to a changing market are the ones that will thrive into the future.
And to get that right, they need timely, meaningful and accurate answers to questions like:
In the past, we relied exclusively on backward-looking tools like financial statements, customer surveys, legacy data warehouses and market research to answer these questions. Today, however, we can answer many of these queries in real or near-real time, thanks to an explosion of data available to businesses, as well as the maturing of tools used to process, manage and analyse this data.
Data, in its pure form, is white noise. But with the right tools and processes, an organisation can tune out the noise to find signals that are meaningful to its business. These signals take the form of actionable insights into an enterprise’s people, operations, customers, markets, finances and assets. Equipped with the right insights, an organisation can make better decisions and grow its bottom line.
Although many SMBs understand the value of data, they are not sure where to begin in building a more data-driven business. One of the most common mistakes enterprises make is to think that technology is the starting point. However, the right place to start is with a conversation about the enterprise’s strategic objectives and which questions it needs to answer to meet its goals.
This will couple the data strategy to tangible business metrics from the outset. The next step might be to prioritise one or two of these questions for proofs of concepts. For example, most SMBs want to make better use of their sales and marketing assets to grow their businesses. There may be low-hanging fruit in identifying which customers are most profitable as well as ways to get more wallet share from them.
The next step is to decide which data will help answer the question the business has in mind. One of the primary challenges is that there is too much data rather than too little. Computer systems and Internet users generate enough data every minute to fill a large library several times over. But most of that data is noise because it’s irrelevant, of poor quality or lacking the context we need to make sense of it.
A thorough assessment of the data a business has at its disposal should not only focus on what is available, but also how trustworthy and relevant it is. There is plenty of data available in website analytics, customer relationship management, point of sales and other platforms in the business, but some of it may be outdated, inaccurate or inconsequential.
The picture is complicated even further by the deluge of real-time data generated by Internet of Things (IoT) devices and the easy availability of data from public sources such as government databases and social media. There is a science and an art to discerning which of this data can help a business to answer its questions with an actionable insight. Getting to that actionable insight is all about the ‘Why?’ factor.
There is plenty of data that explains what is happening, when it happened and how it happened. However, without understanding why something happened or why a trend is unfolding, a business cannot act. A fashion retail chain might, for example, notice a surge in purchases of a locally manufactured jacket.
But without understanding whether this was because of a successful marketing campaign, pricing, or patriotic support for a local brand, it will not be able to act on the data. This is where there is a growing role for unstructured data such as email conversations, social media posts and video content in providing context for why people decide to make a purchase or leave a company.
For data to be transformed into actionable insight, it should provide a credible explanation for a trend or action, as well as offer guidance about what to do to get the best outcome. The criteria that make an insight actionable include:
Making an insight actionable lies as much in presentation and packaging as it does in getting to the right data. How the insight is communicated via visualisation and storytelling will play a large role in determining whether it gets put to good use. Gifted data scientists can make data sing, but there are also powerful self-service reporting tools that enable senior executives to generate their own insights.
To bring a data strategy to life, an SMB may need to harness cloud platforms or invest in new data centre technologies. It will also want to explore which machine learning, artificial intelligence, analytics and reporting tools best meet its requirements. Forward-thinking SMBs will use this as an opportunity to start moving away from data siloes and towards democratisation of data.
But perhaps even more importantly, they will look at the people challenges they will face. If it is their goal to become more data-driven in operational and strategic decision-making, they will inevitably face the challenge of reskilling employees and hiring expert resources. A good starting point is to look at which skills the business has and which it lacks.
This isn’t just about hiring statisticians and techies, but also about creating a data-literate workforce able to exploit the full value of data. It’s also about instilling a culture of data-driven decision-making, where insights are used to empower people and foster collaboration. SMBs should encourage people to share data and insights across department boundaries in support of such a culture.
As they roll out their data strategies, wise SMBs will bear in mind that collection, processing and usage of data isn’t a purely internal matter. Consumers, regulators and the government are becoming more concerned about data privacy and how personal data is used. To earn their trust, companies need to use data in a responsible manner and build a data ethics framework from the outset.
This isn’t just about compliance with data privacy laws such as South Africa’s Protection of Personal Information Act (POPIA) and Europe’s Global Data Protection Regulation (GDPR). It is also about displaying that an organisation has customers’ and the wider community’s best interests at heart. People will be less willing to entrust personal information with companies they don’t trust.
An SMB without a data strategy and a culture of data-driven decision-making is like a person without a nervous system to process the stimuli in the world around them. To survive and thrive in a complex and fast-moving world, SMBs need access to insights that help them sharpen their competitive edge, optimise their businesses, and drive profitability during difficult times.
Data is pouring into SMBs’ IT environments in higher volumes and at accelerating speeds. Managing the vast amount of data they need to retain for compliance purposes or wish to leverage for analytics is becoming an expensive headache for many businesses. It’s the Goldilocks problem: provisioning storage that is just right, neither overspending on unneeded capacity nor falling short unexpectedly.
While the cloud offers a scalable, consumption-based alternative to on-premise storage, it’s not suitable for every application. Challenges such as application latency, legacy systems and regulatory compliance means that not all business systems and the associated data can be easily migrated to the cloud.
That’s where the storage-as-a-service (STaaS) model closes the gap. Available from most major enterprise storage vendors, STaaS offers a cloud-like, consumption-based experience for on-premises storage systems. With STaaS, SMBs can lease storage equipment on a subscription basis and pay only for the resources they use.
This transforms storage from a capital expense into operational expenditure. This can help an SMB to stretch its IT budget further at a time when capital budgets are under pressure. Furthermore, it can bring more transparency and predictability to storage spending—especially when vendors offer value-adds like advanced monitoring.
Overall, STaaS should make it easier to deploy, manage and upgrade infrastructure. SMBs will have the flexibility to scale and refresh their infrastructure as necessary—without the long procurement cycles associated with on-premises infrastructure. They will have more control over their systems and data than they would with a public cloud solution.
The model is still relatively new, so vendor pricing and offerings vary widely, complicating comparison shopping. A company that goes the STaaS route may need to commit to minimum base capacity and contract lengths, so it’s important to navigate the offers carefully. This is where the counsel of a reseller or systems integrator can be invaluable.
When companies start dipping into big data, a common mistake is to head straight for the data itself. The sheer array of data available, not to mention the possibilities for collecting new data in the future, is incredibly exciting. But when your first thought is, ‘Hmmm, what data can I get my hands on?’ (accompanied by evil-genius-style hand rubbing), you’re already missing the enormous potential of big data.
Instead of focusing on what data you already have or what data is available out in the big wide world, start by working out exactly what it is you want to achieve in your business. Are you looking to decrease staff turnover? Improve product development? Understand more about your customers? Each of these objectives requires a different approach and, you guessed it, different types of data.
When you know exactly what it is you’re trying to achieve, only then can you turn your attention to the data (or combination of data) that can help you do that.
Treat big data like any other big business investment, such as expanding into a new retail location or upgrading your manufacturing equipment. You wouldn’t jump into either of those things without a lot of careful thought about what you want to do and why. For instance, you’d probably set out the pros and cons, weigh up the costs and benefits and make a clear business case for the investment.
It’s exactly the same with data.— Bernard Marr in Big Data For Small Business For Dummies5
Using Analytics Better Decision-Making, Towards Data Science, December 1, 2018.
New Research from Accenture and Qlik Shows the Data Skills Gap is Costing Organizations Billions in Lost Productivity, Accenture, January 22, 2020.
Data-Driven Businesses Vastly Outperform Peers, Just Style, November 19, 2020.
Big Data For Small Business For Dummies, Bernard Marr, December 18, 2015.