Big data’s ‘big’ is misleading. Just like being a big man doesn’t always mean you’re a wrestler, same way big data is more about the wide variety of data more than the volume. So, even if, you are a small or mid-sized organization, you can still reap the benefits big data.

How big is big?

It actually really depends on the organization’s size, for example; if you are a local grocery chain, you will not have as much data as Walmart. But you have useful data and a good amount of it all the same. You have information about your customers like their purchase history, track of market fluctuations and marketing strategies. You have a lot of internal operational data as well, like the HR, employee data, policies and compliances. To really leverage this data and to monetize it, you need big data analytics.

Never too small for big data

When we talk about big data we actually talk about data analytics. What analytics does is to find the right little data hidden in a lot of big data. This little data is actionable business insight which can help you to improve your business or to solve business challenges. Let’s say the demand for a specific product or vegetable has suddenly gone down. Using big data analytics you can find out what is the problem with it. Has it been priced wrongly? Have you targeted the wrong section of people? This will help you solve the issue within a few days rather than waiting it out long for the market to change. Instead you can change your strategy. So, the basic requirement is to find these little data which is relevant from big data, for that, you can never be too small for big data.

Variety, velocity and veracity

Velocity is a game changer for any kind of data sets in any size of company. Depending on the number of synchronized data sources you have, you will gather a variety of data pouring in at different pace.  The world is working on real-time, if polka dots are a trend right now and people are talking about it on social media, then you need to start selling them now, not wait for a month assessing the market. People have become more fickle minded about their choices than ever and you need to catch on to it fast. In the time of multi-channel enablement and smart connected devices, you are getting a lot of information on a daily basis in various forms. This variety and velocity may overwhelm you and you may not be ready to tackle it with the speed required. Data analytics will get the insight that you need from data sets and help you make decisions faster and in real-time.

Difference between gibberish and actionable data

Not all the data that is collected on a day to day basis is useful for businesses. Actionable data can get trapped under the amount of accumulated data. Big data analytics will help you fish out the actionable insights from the data that you do not need. Finding such data without proper analytics is like looking for needle in a haystack in this era of connected devises, where data is pouring in from multiple directions and forms.

Big data analytics and monetizing data

Even small and mid-sized companies can have jumbled data that big data analytics can unscramble to find insights to solve business issues.

  1. Less time to market will save time and cost: Doing the required tests, visualizing market scenarios and putting your decisions and products in them to see what might happen is easier with big data analytics. Say you are launching a medicine, find out what percent of people will use it regularly, which market segment will fluctuate and when, before you launch it. You don’t need huge amount of time consuming market research or online and offline survey. Also, you can gauge the market reaction faster by analyzing your sales data and take appropriate marketing measures.
  2. Talent analytics for better workforce: With big data analytics applied to your internal operations like HR you will be able to sort through various candidatures and find the people with the right skills to fit you requirements. It will also help in assessing employee skills and output and plan rewards accordingly and restrict turnover.
  3. Market better: If you have quite a clear view of your targeted market segments, it is obviously easier for you to find better ways of marketing your products to your customers ensuring better revenue. If you are selling honey in a specific area, and your data analytics tells you that the health conscious youth of that part should be your target market, the marketing team can device personalized offers and targeted messages for the crowd.
  4. Maintain well with big data and sensors: Whether they are equipment or vehicles, installing sensors to collect data about the hardware will make you aware of the condition of things. This will enable you to upgrade old, install new and recycle things depending on the need. Sensors fitted to a manufacturing unit’s equipment can help you find which machine is lagging behind, why and what to do about it. If you are a transport service provider then sensors fitted to your vehicles and analytics of the data gathered from them will let you know about the usage, demand and condition of different vehicles.
  5. Invest right: All customers don’t bring the same value. Nor do all equipment. Analyze customer lifetime value and the need to invest in equipment before you invest using big data analytics. Check the market fluctuations and changes in real-time before you invest ensuring your strategies make the most of the present scenario.

As small or mid-sized company, the concept of big data can be overwhelming. It is when you take cues from how others are applying it and understand that big data analytics is such a flexible concept that it doesn’t need an ocean of information to thrive, will you find your answer to using big data the way your organization needs it.