Thanks to advancements in technology, our digital lives are producing expansive amounts of data on a daily basis.
In addition to this enormous amount of data that is produced each day, the diversity of data types and data sources, and the speed with which data is generated, analyzed and reprocessed has increasingly become unwieldy.
With more data continuously coming from social spheres, mobile devices, cameras, sensors and connected devices, purchase transactions and GPS signals to name a few, it does not look like the current data explosion will ebb soon.
Instead, investments in IoT and advanced analytics are expected to grow in the immediate future. Thinking back, investing in advanced data analytics to generate well-informed insights that effectively support decision making and drive business performance have been the paragon of big corporations.
And smaller businesses and organizations, as a result, have for some time embraced the flawed view that such investments are beyond their reach. It’s no surprise then that adoption has been at a snail’s pace.
Thanks to democratization of technology, new technologies are starting to get into the hands of smaller businesses and organizations. The solutions are now being packaged into simple, easy-to-deploy applications that most users without specialized training are able to operate.
Further, acquisition costs have significantly reduced thereby obviating the upfront cost barrier, that for years, has acted as a drag on many company IT investments.
While the application of data management and advanced analytics tools is now foundational and becoming ubiquitous, growing into a successful data-driven organization is about getting the right data to the right person at the right time to make the right decision.
Distorted claims such as data is the new oil have, unfortunately, prompted some companies to embark on unfruitful data hoarding sprees. It is true that oil is a valuable commodity with plentiful uses. But, it is also a scarce resource not widely available to everyone.
The true value of oil is unearthed after undergoing a refinement process. On the contrary, data is not scarce. It is widely available. Nonetheless, akin to oil, the true value of data is unlocked after we have processed and analyzed it to generate leading-edge insights.
It’s a waste of time and resources to just hoard data and not analyze it to get a better understanding of what has happened in the past and why it has happened. Such insights are crucial to predicting future business performance scenarios and exploiting opportunities.
More data doesn’t necessarily lead to better decisions. Better decisions emanate from having a profound ability to analyze useful data and make key observations that would have otherwise remained hidden.
Data is widely available, what is scarce is the ability to extract informed insights that support decision-making and propel the business forward.
To avoid data hoarding, it is necessary to first carry out a data profiling exercise as this will assist you establish if any of your existing data can be easily used for other purposes. It also helps ascertain whether existing records are up to date and also if your information sources are still fit-for -purpose.
At any given time, data quality trumps data quantity. That is why it is important to get your data in one place where it can easily be accessed for analysis and produce a single version of the truth.
Unlike in the past where data was kept in different systems that were unable to talk to each other making it difficult to consolidate and analyze data to facilitate faster decision making, the price of computing and storage has plummeted and now the systems are being linked.
As a result, companies can now use data-mining techniques to sort through large data sets to identify patterns and establish relationships to solve problems through data analysis. If the data is of poor quality, insights generated from the analysis will also be of poor quality.
Let’s take customer transactional data as an example. In order to reveal hidden correlations or insights from the data, it’s advisable to analyze the information flow in real-time; by the hour, by the day, by the week, by the month, over the past year and more. This lets you proactively respond to the ups and downs of dynamic business conditions.
Imagine what could happen if you waited months before you could analyze the transactional data? By the time you do so, your insights are a product of “dead data”. Technology is no longer an inhibitor, but culture and the lack of leadership mandate.
As data become more abundant, the main problem is no longer finding the information as such but giving business unit managers precise answers about business performance easily and quickly.
What matters most is data quality, what you do with the data you have collected and not how much you collect. Instead of making more hay, start looking for the needle in the haystack.
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