‘Big Data’ has become yet another techy, trending, industry-wide buzzword that most of us know is important but find difficult to grasp. Data Science, Data analytics, data mining, etc., are still seen as things technical experts do, not something small and medium-sized enterprises are meant to dabble with.
Such a reaction is natural, given that Big Data is indeed a big deal. But as time and technology change, businesses, both big and small, are finding ever more unique and powerful ways of using data to improve their operations. By 2025, annual global revenue for the big data analytics industry is estimated to reach around a whopping 68.09 Billion USD, and that’s just the analytics industry itself. The returns generated from applying Big data analysis across multiple industries might as well be beyond measure.
So clearly, Big Data is widespread, and it seems to be working out for those that manage to utilize it meaningfully. This raises the question: How can Big data for small businesses be practical? How can growing businesses take advantage of emerging Big Data analytics and practices? If at all.
What is Big Data?
Let’s start with the basics.
Big data represents large data sets that are too big to be processed and analyzed manually or via traditional data-analysis techniques. Loosely speaking, the term ‘Big Data’ often indicates the practice of analyzing these massive databases to draw meaningful marketing and business insights.
Almost all of our internet activity leaves behind a digital footprint. Consequently, recent growth in digital activity has led to an exponential growth in data. Big data is all around us, and most of our online (and even offline) actions generate data in one way or another. From our Social Media activity to our shopping preferences and our browser cookies to our precise geolocation, everything feeds the ever-growing hunger for Big Data.
But does every bit of data online count as Big Data? Certainly not. Big Data doesn’t simply mean large quantities of data; the quality (and a few other dimensions) matters as well. For Instance, Big Data has traditionally been characterized by its famous 3 Vs, namely, Volume, Velocity, and Variety. To put this in understandable terms, Big data refers to data that arrives in larger sizes, at higher than average speeds, and is sufficiently diverse to provide valuable information once processed or analyzed. But at the same time—on account of the 3 Vs mentioned—Big Data becomes unmanageable by traditional data analytics techniques and systems.
What is the Importance of Big Data Analytics?
Big Data’s importance is fairly straightforward. The more data companies have access to, the better they can optimize their operations and improve their customer’s experience.
Traditionally areas like marketing and product development have benefited the most from leveraging Big Data insights—since these are fields that have the most to gain from clearly pronounced data trends and user insights.
Brands like Amazon and Netflix are great examples of applying big data analytics to identify customer preferences better and boost engagement and retention.
However, Big data’s utility spans beyond just the consumer side of the business. Even unorthodox and unexpected areas like supply chain management and employee engagement benefit from Big Data.
Businesses equipped with data-driven market insights, for instance, can better predict ever-fluctuating demands that threaten most markets. Add to that a company’s ability to optimize their supply chain to suit such changing demands better while maintaining appropriate inventory levels at the best possible cost, and you have a massive data-backed advantage over your competitors.
Big Data for small businesses has thus grown way beyond just being an option, an extra step that brands could opt for. Instead, it has now turned into a necessity.
Is Big Data for Small Businesses Practical?
While Big Data’s advantage to companies that utilize it might be evident, what isn’t evident is if the same benefits translate to smaller and medium-sized businesses.
- Do smaller companies have enough customer and operations data for a Big Data setup to be viable and worth the investment?
- Should they focus on employing Big data experts and building the required infrastructure this early on in their business?
- Is it better for start-ups to begin with a data-driven approach or to slowly adopt Big data practices as the companies grow?
These are difficult questions with no straightforward textbooks answers. However, completely ignoring any form of data analytics is certainly not an option.
Because larger corporations have massive amounts of data as well as the resources to make significant data mining and analytic efforts, it must be no surprise that the bigger players are sure to ride the Big data wave to ever-growing profits and efficiency.
On the other hand, smaller companies without a Big data strategy are much likely to struggle against larger competitors that rely upon Big data. Given such market conditions, perhaps depending on Big data themselves is the only way emerging companies can remain competitive.
Major Challenges in Utilizing Big Data for Business
Yes, Big Data offers massive benefits and small businesses cannot afford to ignore it anymore, but utilizing Big data for small businesses doesn’t come without its own challenges.
The three major challenges small businesses face when it comes to utilizing Big Data are as follows:
- Cost of implementation
- Finding the right expertise
- Cultivating a data-driven culture
Let’s discuss these in detail.
Cost of Implementation
Big Data doesn’t come cheap. Massive servers with terabytes of data, sophisticated tools that identify trends and patterns within the said data, and experts that oversee the entire operation; all call for a significant investment.
For a tiny firm, big data can be too big of an investment.
More than 90% of all businesses believe they must be opting for data analytic solutions. The global big data and business analytics expenses for 2021 are expected to be around $215 Billion, which is likely to make you wonder if businesses are spending a bit too much on Big Data and if small businesses can afford such extravagant solutions.
Maintaining a healthy ROI is yet another challenge. Investing in Big data analytics doesn’t necessarily imply greater profits and better efficiency.
Beyond that, businesses need to ensure they are reading the correct data, under the right parameters and constraints, for the right trends. Simply diving headfirst into massive datasets, looking for anything and everything can be counterproductive and expensive.
Finding the right expertise
Perhaps the only thing more difficult than finding cheaper yet effective ways of implementing Big data analysis is finding the right and reliable people that can do it for you. Data scientists are still in high demand and considerably rare to find.
Analysts todays use a whole host of techniques, practices, languages, platforms, and tools to carry out comprehensive data analysis, meaning your average marketing team isn’t going to cut it. If you want to be serious about Big data, you’ll need to hire experts.
Then again, hiring or training a team of data scientists is simply not feasible for a lean start-up or even a medium-sized brand that desires data-driven solutions on a budget. Thus finding the right expertise while balancing the expense for the same is a massive challenge for emerging businesses.
Cultivating a data-driven culture
A 2020 article from the Harward business review stated, ‘the biggest obstacles to making data-based businesses’ or as we say it, to making data-driven business decisions ‘aren’t technical; but cultural.’
When companies think of Big data and data analytics, they often consider incorporating an additional team or division into their usual operations. However, considering how competitive the markets have got in terms of data analysis, modest efforts like these might not be enough.
What businesses need instead is to incorporate and nurture a data-driven culture within their organizations. This isn’t to say that a data-driven company is entirely about numbers, far from it. Instead, such a business recognizes the value of data-based insights and incorporates them into the very ethos of the company.
A data-driven approach inspires organization-wide relevant decisions and operations to be backed by facts and data. It also ensures overall efficiency and optimization in every aspect of the business.
A data-driven business culture guarantees that Big Data’s benefits do not remain confined to the realms of marketing, sales, and customer services. Rather they bring a data-oriented approach within the entire business, ensuring the company reaps much greater Big data benefits than what was first imagined.
But bringing about such a radical change within a working business is no joke. While almost every business would prefer being built upon a data-driven culture, most only manage to incorporate data analysis to the extent of buying some data analysis tools.
Much of data’s ability to transform an organization’s operations is often left untapped in traditional data analytics divisions.
A Roadmap for Small Businesses Implementing Data Analytics
It might be tempting to assume that Big Data for small businesses (or even for medium ones) simply isn’t a viable option. But despite the challenges, data analytics isn’t entirely off the table for emerging companies.
Small businesses can do Big Data the ‘small’ way and still manage to extract major benefits. Granted that the scale at which a company like say, Amazon, runs its big data operations is simply unmatchable when compared to what your local super-market could ever manage to do. But tiny businesses can still leverage data analysis on their own scale to produce meaningful results.
Below is a roadmap or a blueprint, if you will, that breaks down how smaller companies can go around utilizing Big Data into five macro steps. These are all about maximizing results for tiny businesses while respecting their limited budget and resources.
Learn to Get Data the Right Way
To execute any Big Data strategy, you’ll have to ensure you have access to the best quality data available. Not all data is equally valuable; neither is every type of data suitable for your specific goals at all times. More than that, getting the right data can often prove to be very expensive. Thus, when it comes to data, small businesses need to get creative.
The good news is that most small businesses already have access to a ton of data; they just need to find ways to tap into it. There are three basic ways in which small businesses can acquire meaningful data:
Basic Analytics:
These are your web and social media analytics. Simply going through your site’s analytics and digging into how your posts have been performing can give you invaluable insights into your business and marketing campaign. The best part is that both of these data sources offer enough depth in terms of data quality and quantity. Such analysis can allow you to uncover upcoming market trends and discover what’s working best for your business.
Independent research:
To further step up your data game, there is always the opportunity for deeper research. Small firms can rely on targeted and specific research methods like rolling out audience surveys, questionnaires, and even case studies! These may not necessarily qualify as Big data, but they are an excellent way to bootstrap your research initiatives. When it comes to data, quality far outweighs quantity. For companies wanting to go the quantitative route, deploying data harvesting tools to gain insights into your business operations is also a viable alternative.
Buying data online:
And finally, to go as big as you can with Big data, you always have the option to buy data online. Although not every bit of data available online is relevant to you, neither is all of it reliable or legit. Be very specific with your data needs and ensure you get it from market-trusted sources. Ensure you know exactly what you are looking for and avoid wasting time and resources on data sets and trends that may not be relevant for your business.
Bear in mind these are not the only way to go about gathering data, rather these are the most generalized and actionable ways to do so. For those looking for business-specific data collection and processing methods, experimentation is the key. Approach data collection as an exciting opportunity with an open mind, find creative ways to learn more about how your business operates, and improve on those areas iteratively.
Picking the best tools for your needs
Once you get your hands on the best data you can find, the next step is to identify the right tools and software to make the out of your Big Data initiatives.
You can opt for enterprise solutions, that allow you to harvest, integrate, organize, process, and even visualize all your data under a single platform. Or you could go with reliable but minimal solutions like google analytics and Microsoft Excel, depending upon your budget and ambitions. There is a middle ground as well with popular free and open-source data analytics tools, but everything comes with its own pros and cons, of course.
Remember, not every tool is meant for you, nor every software you spend money on will be worth the buck. Take some time to find the right tools at the right price that fit your personal needs and goals best.
Getting a Big Data Team on a Budget
Having all the right data, tools, and strategies in the world won't mean a thing as long as you don't have the right people to make use of them. Hiring Data scientists is no joke, and for start-ups and growing businesses, it isn't even affordable.
Given that your Big data needs will be fairly limited, at least when starting out, training your current staff for the task or outsourcing your analytics needs can be two viable options. Since hiring a data scientist full-time is not an option.
There are plenty of resources available online to get started with Big Data. Or better even, you could hire a Big Data analytics company to do the job for you.
Again the choice depends on your budget as well as on how far you are willing to go down the Big Data route, but remember that you always have the option to expand your team later on if the need arises.
Developing a data-driven culture
If every company is a data-generating tech company, every employee might as well be a data scientist. We now inhabit a digital world built and run by data, but businesses need to code this awareness into their very ethos to qualify as a data-driven company. Here are a few tips on how companies can achieve this:
Start with the leadership:
When implementing an organization-wide change, a top-down approach works the best. Rather than relying on the ones at the bottom of the hierarchy, a data-conscious leadership sets data-oriented goals and expectations, supporting the adoption of a new mindset.
Democratize the data:
Any organization's data is valuable and sensitive, as a consequence of which, companies often end up gatekeeping it. Sometimes even from their own employees. Needless to say, such practices do not encourage a data-friendly culture. Allowing employees to access the organization's data strategically can help them better grasp how the business operates.
Results speak for themselves:
Cultivating a data-driven culture is incredibly important if you want to transition from a company that does a bit of data analytics on the side to a company that is fundamentally driven by data. And once you start going down the data rabbit hole, you'll begin to notice the difference as well as why it's essential to be the latter.
The good part is that once your team gets the hang of incorporating data-backed facts and insights into their workflow, they'll begin to see the tremendous difference a good data strategy can make. Rather than enforcing a strategy your team needs to follow, you are better off giving them a free hand to experiment and incorporate data within their work as they see fit.
Such an approach is likely to inspire creativity and trigger a results-based positive feedback loop, ensuring your team utilizes the best data practices and knows why it is important to do so.
Experimenting and Iterative Improvement
And finally, remember that there is no right or wrong way to do data analysis. There are best practices for sure, but every business is unique and no two data sets are the same; so figuring out the right data strategy, much less extracting insights relevant to your business, will take some work.
A general guide I recommend is Metrics, Patterns, Questions, and Insights. What I mean here is that companies need to focus on these four key areas when coming up with their data strategy.
The first step to data analysis is picking the right Metrics. The problem with data analysis, even for small businesses, isn’t that there is not enough data to go around but that there might be too much of it. Knowing precisely what you are looking for, certainly helps. Identify relevant metrics to your business and build your strategies around utilizing them.
Say, for instance, you are a local supermarket wanting to incorporate data analysis. Tracking your average basket size or average transaction value might be more important than tracking your inventory turnover in certain cases. Ideally, you want to do it all, yes, but realistically when on a tight budget, you’ll have to choose and select what you want to track.
Preliminary analysis of chosen data will reveal emerging trends and patterns which can unveil relevant insights. But remember, trends and patterns by themselves are useless unless you start asking the right questions about them. Start asking why a particular trend might have emerged and how that knowledge helps you achieve your goals better.
For instance in our supermarket example, if your average basket size shrinks during winter, for instance, it might be because shopping habits are changing over the seasons in ways you can’t keep up with. Armed with this knowledge, you can now find better ways of adapting to these changes. To know more about specifically applying Big Data in retail, check out what the experts have to say on the same.
Asking the right questions and finding ways of leveraging those answers is as important as harvesting and analyzing data itself. Rather than following popular advice word by word, be open to experimenting with your data strategy to figure out what works best for you. The whole point of practicing big data analytics for your business is to figure out specific strategies for your business, so feel free to experiment.
To conclude
Big Data presents itself as a massive opportunity every business worldwide can tap into. But despite its popularity and effectiveness, most businesses still struggle to find the right ways to harness Big Data.
One could even argue that Big Data is simply too big for small and growing businesses to take advantage of. But the takeaway here isn't that Big Data for small businesses is not viable, but instead that these emerging businesses can and should find creative but effective ways of incorporating data into their operations.
Doing so is never easy, but having a clear data-oriented approach and working to build a data-driven culture can go a long way. To sum it up, as a small business entering the Big Data world, you'll have to get your priorities straight, know precisely what you are looking for, strategize around your priorities and be careful around how you execute your data strategy.
As tough as it may sound, it isn't just possible but highly recommended that small businesses get involved with Big Data. With the right mindset and calculated efforts, your data analytic efforts will undoubtedly pay off.
