Well, how amazing is that!
But do you know what’s even more amazing?
The sheer potential of Data-driven Analytics as a tool for businesses and the reluctance of the companies to adopt data analytics for improving their business prospects.
According to research, data-driven enterprises are three times more likely to make successful business decisions compared to other organizations.
Meanwhile, another research conducted by Gartner, a Technology Research and Consulting Company reveals that 87% of organizations are classified as having low maturity levels in terms of business intelligence and analytics capabilities because 97% of the data sitting with these institutions are not being analyzed.
Moreover, businesses are not adopting data analytics for making better decisions and identifying opportunities. They are acting on intuition to make business decisions. And this severely affects the productivity and the success of a business.
Intuition or Data?
A good intuition might help identify and execute highly profitable decisions in a business environment. But when the stakes are high especially in a business, intuition should always be backed by solid data. Using intuition with data is the combination that every business should adopt to succeed.
Although the answer to the question of why a business should adopt Data analytics is implicit in the above facts, we think a little more insight into the topic will be a lot more convincing.
Therefore, let’s look at Data Analytics and Why is it of Interest to Companies.
Why Data Analytics?
We live in a world where the Internet is no longer a noun but has become a verb. Where millions of transactions are taking place over the internet, mountains of data are being produced every second.
And this data is not just a pile of information, it is almost as precious as gold to businesses because this data contains various purchase records, user interests, spending habits, product preferences, personal information of potential customers, and tons of other useful stuff.
This data can help companies in countless ways if they can churn out the relevant information from the pile and integrate it into their strategies. Data Analytics is the tool that will help these businesses extract the value out of the data and boost their performance.
As already mentioned, businesses can make three times more effective decisions using data analytics and that translates to more sales and revenue, more efficient functioning, greater success rates for new ventures, and above all a more confident business.
Therefore, it is counter-productive for a business to exist in denial of the rapidly changing ecosystem. After all, you won’t expect to win a motor race on a horse, will you?
Hence, every business must change according to the need and keep innovating. Because if you are not willing to change, someone around the corner is more than happy to take your place.
So why let this opportunity pass?
Why not embrace it with open arms and let it guide you through the hallway of success and prosperity?
Is Data analytics really of interest to companies?
At this point, the answer should be obvious.
How to be more Data-Driven?
Now that we have resolved the issue of whether Data-driven analytics is of interest to companies or not. Let’s look at how to be more Data-driven.
1. Select a High Potential Goal and Devise a Data-driven Strategy around it
Identify a high-yielding opportunity that looks promising and use the data at your disposal to meticulously plan a strategy to achieve your goal. Data analytics will provide you with the insights you need, to target the vital spots and make an impact.
Data analytics will help you take the first step in the right direction and without Data analytics it’s just a free hit and trial, you try a strategy, see if it works or not, and move on to the next strategy if it doesn’t until you find the right strategy.
It makes the process more efficient for you and in turn increases productivity and boosts performance.
2. Don’t go all out at once with Data Analytics
Although the evidence clearly suggests that Data Analytics is of high interest to companies, there is no need to employ data analytics on the entire organization all in one go.
A business has various departments and every department has different goals and priorities. So the transition to a data-driven enterprise might not be as smooth for every department.
Therefore, it would be a good idea to first demonstrate the potential of Data analytics on a high ROI project and lead other departments into a more data-driven environment through the results.
3. Treat Data as a Strategic Asset
Data is highly valuable and should be treated as a strategic asset rather than a resource with limited access that must be stored.
It helps companies strategize and boost productivity, and if data in the organization has limited access, then the extent of its utility to the business is capped as well.
Data should have centralized access and all the departments and units of the organization must leverage the data to achieve discrete goals with high efficiency, which in turn will boost the overall productivity and output of the business.
4. Induce Individual Data-Drivenness
For the business to transition onto a data-driven organization, the change needs to come on the individual level. If the employees in the organization develop a data-driven approach, then the cultural change will reflect in the entire organization.
Indulge the employees in problem-solving exercises using data and offer incentives to the top performers. This will help them develop a core understanding of Data analytics.
Companies should offer basic courses on data analytics and data science for employees. And also offer interested employees to carry their training forward into professional courses. Because in-house Data experts will prove to be pivotal to the success of the data-driven campaign.
What are the Key Challenges that Businesses Face while Transitioning into a Data-driven Enterprise?
A recent study from the Harvard business school reveals that 77% of the executives report adoption of Data-driven analytic techniques is facing major challenges. It is not just the company that has to accept the Data analytics but its employees need to accept the cultural shift as well.
Even when companies acknowledge that Data analytics is of interest to them and decide to transition. The real challenge lies ahead.
The key challenges are–
1. The cultural shift
Even after the company decides to accept data analytics, a study shows that more than 70% of the companies fail in making the transition because of the lack of Data drivenness of the employees.
A sudden change in regular workflow and decision-making may lead to resistance from the workforce and outright denial of the new methods.
To avoid this, the leaders should employ Data-Driven Decision Making in their projects. And lead their team members through the results. Keep in mind that the transition will not occur overnight. It will happen gradually as the results start to pile up and everyone starts noticing.
Therefore, the senior executives must inspire and lead through an example if the employees are to embrace the shift.
2. Lack of Skills among Employees and Executives
Data analytics is a complex skill and requires a lot of theoretical and practical knowledge. It has various levels ranging from low to high and to extract valuable insights from the data, and one needs to master all the levels of Data analytics.
Hence, a business that has adopted data analytics will feel the inability to access the potential of the data. This is due to the lack of skills among the employees and executives to harness the data.
The lack of skills is what fuels the lower acceptance rates of Data-driven strategies among the employees.
Consequently, to overcome the challenge free Data analytics courses can be offered to the employees. And a pay hike may be offered for employees who are willing to get certified in professional Data analytics courses.
3. Limited-Acess of Data in the Organization
The limited access to data refers to the low adoption rates of the Data-driven approach in the companies. And the muted participation of the majority of the employees in the decision-making of the organization.
It’s the same as the employees not having any access to the data that can help them improve their performance along with the company.
Because even if they have the access to the data and let’s say they possess the relevant skills to draw insights from the data. It does not make a difference unless they share their insights and suggestions with the relevant departments or executives.
Hence, it is important for the employees to actively communicate their ideas and insights with their superiors. Therefore, companies should encourage employees to be a part of the decision-making and incentivize innovative solutions to problems.
What about the IT Infrastructure for Data Analytics?
When you have dealt with all the challenges and transitioned into a data-driven enterprise, the amount of data in the company will be in billions of bytes and that requires specialized infrastructure and a team of highly skilled IT experts to manage the in-house data centers.
But the major issue with having in-house data centers is that it requires constant updating and this will add up to the operating expenses.
At the initial stage, companies relying on obsolete technologies to collect and process data waste a lot of time. And, as a result, this reduces efficiency and therefore the performance of the organization is affected.
That’s where cloud computing comes into the picture.
Cloud computing refers to delivering online computing services including servers, storage, databases, networking, software, data analytics, and more to the businesses and pay according to their usage.
Companies should prefer cloud architecture over in-house private computing architecture as cloud computing is faster and cost-efficient.
Companies that have already invested in private data centers can align their data with cloud architecture to create a hybrid architecture to shift their data to the cloud and design new data cycles for better optimization of data.
Advantages of using Cloud computing over on-site data centers are–
- Cloud cumputing allows the companies to only pay for the services they use and access any other services instantly according to their needs.
- Online cloud services are faster and are constantly updated to the latest technologies.
- Cloud architecture is very flexible. It allows the companies to have access to the right amount of resources at any time from anywhere in the world.
- It offers better productivity as the companies do not have to worry about maintenance.
- Cloud service providers offer a wide set of security measures that improve the overall security posture of the organization.
Some of the famous cloud service providers are Amazon Web Services(AWS) and Microsoft Azure.
Application of Data Analytics in Various Feilds
The application of Data Analytics is not confined to a specific industry like information technology, software, or food and beverage.
Data analytics as a tool does not have any boundaries when it comes to utility.
Here are some examples of how data-driven analytics is being used across sectors to bring change and improve functioning, be it Finance, automotive, administration, food, and beverages, etc.
If you wish to know more you can read our article on Data Analytics for Finance Professionals.
- KCCI, a Japanese telecom service provider collaborated with Accenture and AWS to collectively develop a Data analytics software after it had reached saturation in terms of subscribers. The goal was to personalize the user experience by getting to know their customers. The software was named ‘ARISE’. It used AI and ML to unearth insights from petabytes of data and helped ACCI personalize the experience for its customers.
- The West Midland Police Department in the UK collaborated with Accenture and AWS to develop the Data-Driven Insight (DDI) program. It used the police records and pieces of evidence to identify crime patterns in the city and profile the suspects.
- Companies like Google and Amazon have their entire business model based on data analytics. And both the business models are quite successful so it is safe to assume that data-driven analytics is good for business.
There has been a 100 fold multiplication in the number of new data points over the internet in the last decade. And every new data point is capable of connecting to all the other data points. Thereby, giving us a 10,000 fold multiplication in the number of new patterns that can be observed.
Every day 5 quintillion bytes of data are created over the internet around the world. Just to give you an idea of how big that number is, we will write it down for you.
And in the coming years, this number will grow exponentially. It would be a wise decision to double down on this opportunity as a company. And use data analytics to analyze this gigantic mountain of data and mine the value out of it.
Advantages of Data-Driven Decision Making (DDDM)
As a business, there are numerous advantages of using Data-Driven Decision Making. Here are some of the reasons why data analytics is of interest to companies.
- Using data-driven analytics allows companies to identify trends and opportunities before their competition and give them a headstart to capitalize on the opportunity.
- It helps the companies to improve efficiency and reduce costs.
- Data analytics helps companies to drill into granular data and extract hidden insights that cannot be accessed using other tools.
The value that Data-driven analytics offers to companies is irreplaceable. No other tool could possibly boost the prospects of the company like data-driven analytics. Moreover, data-driven analytics is a golden fabric that can be imbued with the success stories of the companies if used in the right manner.
Having access to data-driven analytics and not using it to carry the business on the path to success is similar to having wheels on your rolling luggage but lifting it instead of rolling it down the hallway.
We hope that now you are more aware of Data Analytics and Why is it of Interest to Companies.