{"id":11701,"date":"2020-05-08T03:48:23","date_gmt":"2020-05-07T22:18:23","guid":{"rendered":"http:\/\/www.allerin.com\/blog\/?p=11701"},"modified":"2020-04-27T03:51:32","modified_gmt":"2020-04-26T22:21:32","slug":"all-businesses-have-become-data-driven-or-have-they","status":"publish","type":"post","link":"https:\/\/www.allerin.com\/blog\/all-businesses-have-become-data-driven-or-have-they\/","title":{"rendered":"All businesses have become data-driven. Or have they?"},"content":{"rendered":"

\"data-driven<\/a><\/p>\n

Data is the most valuable resource for any enterprise. But there are shortcomings in how enterprises are utilizing their data. About 2.5 quintillion bytes of data is generated each day<\/a>, which is equivalent to about 100 million blu-ray movie discs. And even though you have access to possibly all the cinema in the world, you\u2019ll end up watching just a few hundred or a thousand in your lifetime, if you take binge-watching to the next level. Or maybe you\u2019ll get bored soon enough to even watch about fifty good movies. Similarly, with data, even though an enormous amount of it is generated and available to capitalize upon, a fraction of it is utilized by enterprises. Enterprises need to leverage every bit of data that is available to them if they want to accelerate their growth and stay ahead in the cut-throat competition that is seen in every industry. The path to becoming a data-driven organization is difficult, but businesses must embark on it if they want to reach new heights. As mentioned earlier, businesses generate and have access to a huge chunk of data.<\/p>\n

But, are organizations properly utilizing data?<\/h2>\n

The answer depends on the organization, but to sum it up, most organizations fail to utilize the data available to them. Small to medium enterprises usually ignore the capabilities of data. And even businesses that utilize data, they don\u2019t use all of the generated data. The major focus is customer analysis when it comes to utilizing data. No wonder customer analysis is the second most important aspect for business leaders when speaking of data analytics. Similarly, customer analysis is the leading use case of data analytics for enterprises that are technology-based<\/a>. The focus is not much on other core operations, as it should be.<\/p>\n

 <\/p>\n

Additionally, most of the data goes wasted as enterprises feel it is of no value or can\u2019t understand its actual importance. They fail to realize that even the smallest bit of data available can prove highly valuable in the growth of the organization.<\/p>\n

<\/h4>\n

But there are businesses that have realized the true value of data and have implemented tools and measures for utilizing data to its maximum benefit. About 53% of businesses have adopted big data analytics tools<\/a> to improve their operations based on data analytics reports. So, why do a majority of organizations fail to understand the potential of data and utilize it to its maximum?<\/p>\n

Why are organizations unable to utilize data?<\/h2>\n

Most of the data collected by organizations is dark data. Gartner has defined dark data as<\/a> \u201cThe information assets organizations collect, process and store during regular business activities, but generally fail to use for other purposes (for example, analytics, business relationships and direct monetizing).\u201d <\/em>About 55% of the data collected by organizations is dark data<\/a>. Businesses face a large number of shortcomings in utilizing this dark data. These include:\"data-driven<\/a><\/p>\n

Lack of tools to capture data: <\/strong>Most small to medium enterprises lack tools that can be used to capture, analyze, and then generate reports based on the data. Even if they do have a data analytics tool at their disposal, the tool isn\u2019t easy to use and hence results in being non-useful. Data analytics and data utilization thus becomes a liability to the organization instead of being an asset. Once businesses do employ a data analytics tool, they should ensure that the best practices regarding big data analytics<\/a> are followed.<\/p>\n

<\/h4>\n

The data is not good enough: <\/strong>Most of the data captured by organizations is incomplete in terms of the information they provide. Thus, they fail to give the complete picture about a certain scenario and thus prove as good as being useless. For instance, the data captured by a data analytics tool employed by a financial enterprise might have information about a transaction done by a customer, but it won\u2019t have the details regarding the location the transaction was carried out or other important metadata that is associated with the transaction.<\/p>\n

<\/h4>\n

They don\u2019t know where the data is coming from: <\/strong>A large number of enterprises don\u2019t realize that every bit of data is useful and can help in the growth of the organization. Most enterprises simply ignore valuable data that is readily available to them.<\/p>\n

<\/h4>\n

Lack of skill set: <\/strong>Highly skilled data scientists nowadays are a rarity. About 60 percent of businesses find it difficult to hire good data analysts<\/a> when compared with other roles in an organization. The data analysts at most organizations are average, to say the least. They have limited knowledge about interpreting data and utilizing it. Thus, even if an enterprise has a highly advanced analytics tool, it can\u2019t be used to its maximum potential.<\/p>\n

<\/h4>\n

Data is available to a limited part of the workforce: <\/strong>Data analytics and business intelligence tools are generally only available to managers and leaders. The access is limited to higher authorities and employees ranking on the lower end of the hierarchy have barely any access to these tools.<\/p>\n

What can leaders do to develop a data-driven organization?<\/h2>\n

The primary step enterprises can take in becoming data-driven is to start using premium data analytics tools. To reap maximum benefits from these tools, enterprises must hire skilled data scientists and analysts. Although data scientists are hard to find, organizations can spend extra resources and efforts to ensure that they find a good one. The combination of premium data analytics tools and skilled analysts can speed up the process of becoming a data-driven organization. The right combination can help improve the ability to make business-informed decisions quickly and efficiently, backed by facts. Premium data analytics tools help gather every bit of information that is generated by the organization. Thus, organizations will have structured, as well as unstructured data available for analytical purposes. Data analytics tools can also improve the awareness of risks, enabling the implementation of preventative measures at the workplace. Data analysis is also proven to reduce costs and thereby can help in increasing profits.<\/p>\n

<\/h4>\n

Organizations also need to improve data literacy. The access, usefulness, and usability of data should be explained to every employee. Also, the ownership of the data should be defined at every stage. Employees should have a clear understanding of what data they are entitled to access and should work accordingly. Enterprises should also encourage employee feedback and motivate individuals to ask questions regarding the use of data analytics. Although there might be a number of employees working with data, there should be an individual that takes the final business decisions regarding data analysis. Usually, it is the CEOs that should take the leadership role in determining the organization\u2019s data analytics agenda. And as per a survey, about 53 percent of CEOs feel they are the leader of the organization\u2019s analytics agenda<\/a> and make decisions accordingly.<\/p>\n

<\/h4>\n

Becoming data-driven is not all about introducing analytical tools at your workplace. It is also about having employees that can truly utilize data analytics tools and can help extract maximum benefits out of them. Hence, businesses must ensure that they invest in skilled human resources, too, when it aims at becoming a data-driven organization. If organizations ensure these steps are taken, it won\u2019t be long before they truly<\/em> become data-driven.<\/p>\n","protected":false},"excerpt":{"rendered":"

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