The Main Challenges Faced By Data-Driven Businesses

The quantity of data being produced by enterprises nowadays is staggering. Being a data-driven organization means that your company is prepared to base decisions on facts rather than feelings, general observations, or subjective judgment. That implies your company has the data necessary to make decisions that result in favorable outcomes.

 

Yet, being a data-driven firm involves more than just employing data specialists, acquiring and installing the required applications and tools, and putting money into your data infrastructure. Making data and analytics a key component of your company's culture, overarching business strategy, and all business operations is the goal.

 

A data-driven company understands both the value of gathering raw data and the limitations of using it as the only basis for business decisions. Instead, they take the time to gather, examine, and glean insights from the data to manage company problems, identify expansion prospects, and foster profitability. Organizations that are data-driven use data for a variety of things, including customer feedback analysis, observing consumer behavior and purchasing trends, and more. These companies have established a data culture that affects the whole business. It's not simply at the top level or in a few functional areas operating in silos.

 

No matter how big or little, the industry or niche they serve, the goods or services they provide, or the size of the organization, every business creates data and may, as a result, become data-driven. The correct approach and method of execution are what matter.

 

Why is Data important to businesses?

 

Your most valuable asset may very well be data. You may leverage the wealth of information it offers about your customers, their behavior, and market trends to your benefit. When utilized appropriately, it can support your company's expansion and enable Better Business practices that let you operate more productively, doing more in less time, and saving you money.

 

Data-driven businesses don't expand linearly, which is one of the reasons why large tech giants like Amazon and Google record exponential growth. These companies built their whole business models on data.

 

PwC research demonstrates that data-driven businesses may beat their rivals by 6% in profitability and 5% in productivity. According to different research, data-driven businesses are 162% more likely than their non-data-driven rivals to exceed sales targets and 58% more likely to outperform them.

 

And this study reveals that 81% of firms concur that the basis for all business decisions must be data. The figures appear terrific, but it's crucial to keep in mind that raw data isn't necessarily going to be beneficial or instructive right away. You must gather your data properly and change it into something you can utilize if you want to take full use of it.

 

Challenges of Becoming a Data-Driven Organization:

 

Attempts to become data-driven by several companies have been ongoing for a while, with varying degrees of success. This is so because if there are many good reasons to move towards a data-driven culture, there are many obstacles to be overcome along the way. According to a recent poll, the main problem facing businesses developing their data strategies has nothing to do with technology. It has more to do with the reality that organizations and people are reluctant to change.

 

It has been increasingly harder for businesses to switch to a more data-driven approach when you take into account cultural phenomena like the COVID-19 outbreak and the emergence of self-service. Consumers of today may get information and data whenever and however they choose. Customers may select the news sources they follow, the social networking sites they use, and the information they want to believe as information gets more and more decentralized.

 

The structural factor comes into play next, and given that we are producing data at exponential rates, it is understandable why so many firms find it difficult to transform into data-driven enterprises. It gets more and harder for businesses to have a sound data strategy and move towards becoming data-driven as time goes on. Today's businesses deal with enormous new data volumes and fresh data sources every day.

 

Up to 80% of all new data is unstructured, which makes it difficult to acquire and quantify. Big data is an asset that moves through a business, spanning traditional boundaries and sometimes lacking a clear ownership structure. Businesses must understand and value this. The problem of data management is made much more challenging by the fluidity of the data since you need to figure out how to make sure it can continually provide value.

 

It may be exceedingly difficult to run your organization without the appropriate datasets, data analytics tools, and data scientists. This is particularly true for startups that lack the funds to employ a chief data officer (CDO) to manage all of this on their behalf.

 

Challenges That Prevent Businesses From Becoming Data-Driven

 

For a while now, many firms have been making the transition to being data-first operations, with varying degrees of success. This is because despite there being many reasons to strive toward a data-driven culture, there are many obstacles to be overcome. Furthermore, research indicates that technology is not the main obstacle to a data-driven business strategy. It has more to do with the resistance to change that exists inside organizations and among their constituents.

 

The difficulty of becoming data-driven continues to increase, which is not helpful. Companies increasingly deal with enormous new data volumes as well as new data sources, such as texts, sensor data, photographs, signals, and other unstructured data types that are difficult to record or quantify.

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Challenges That Prevent Businesses From Becoming Data-Driven

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1. Cultural Dynamics:

 

Businesses have found it more difficult to switch to more data-driven practices when you take cultural aspects like the development of self-service and the 2020 global health pandemic into account. Information is becoming increasingly decentralized as a result of how and when it is received by consumers nowadays. Because of this, users may select the social networking sites, news sources, and information sources they want to use.

 

The fact that so many businesses struggle to become data-driven is perhaps not unexpected when you take into account the structural component and the exponential rate at which data is being generated. The work grows increasingly challenging as time passes.

 

The ownership and management of data is another issue that is drastically increasing in importance for enterprises today. This guarantees the use of data ethically and responsibly. Recently, this subject has received a lot of attention from critics and has been the focus of much discussion and writing. In general, it may be fairly intimidating without the proper datasets, analytics tools, and data professionals to help your organization.

 

2. Low-Quality Data:

 

Data may be beneficial or bad. One of the main reasons why businesses are reluctant to use data-driven assistance for decision-making is the availability of low-quality data. Poor data may seriously hurt a company's goals and overall decision-making. Poor data quality costs firms, on average, $15 million a year, according to Gartner.

 

Lack of regular and ongoing data collection causes insights based on defective, partial, or erroneous data to be flawed because the data is too noisy and unreliable. So, it's crucial to never take for granted that the data used to inform business decisions is accurate.

 

3. Inaccessible Data:

 

As data is frequently locked up in functional silos and difficult to access outside of the department or application, employees frequently struggle with data inaccessibility. The majority of departments in conventional businesses retain data manually rather than using the system, in contrast to the current automated data management strategy. Because there is no common repository for data, it is difficult for decision-makers to plan and work together as a team.

 

Infrastructure and resources should be available to facilitate data exchange between departments. Also, businesses might have data governance standards that provide a single source of truth for all of their data.

 

4. Lack of System Integration:

 

Data is abundant for businesses. The issue is the enormous volume of unstructured data stored on many platforms. The lack of standardized data gathering procedures and efficient data integrations, which are necessary to maximize the value of this data and provide a comprehensive picture of it, is the root cause of the issue for many firms. Data management becomes increasingly difficult when you deal with additional platforms. 

 

It might be challenging to evaluate and correlate diverse data from many sources spread across functional silos and apps to finally offer value to the business. The organization's capabilities should be increased and productivity should be increased by efficiently integrating a variety of functions, interfaces, and technologies. Thus, it is essential to map the integration of current and future data systems while still in the planning stage.

 

5. Insufficient Data Interpretation:

 

Getting a thorough picture of the diverse data is essential for good interpretation as the number of sources rises. Strategic planning is hampered by poor visualization, which makes it difficult to grasp data on inventories, staff performance, production, vendors, or financial transactions. Additionally, it is challenging to find pertinent data points to aid in decision-making since traditional systems are unable to proactively analyze real-time data to get insights into business operations.

 

6. Lack of Actionable Data Insights:

 

The potential of automation tools like AI and machine learning to acquire quicker and better insights cannot be unlocked due to a lack of proper analytics skills. Organizations may employ AI-powered data systems to automatically expedite the aggregation of data from diverse sources, identify trends, connect data points, and understandably display data so that real-time insights can be applied to business decisions.

 

7. Absence of skills and a culture that values data:

 

More than just the correct technology and strategy is required for a business to become data-driven. Companies can only adopt a data-first culture successfully if they want to become data-driven. To create a data-driven culture and deal with circumstances when workers make choices based on feelings rather than data-driven facts, most businesses still struggle. A data-driven culture requires skills as well since it should start with the C-suite executives and go across every department of the company.

 

Conclusion

 

For many firms, the transition to a data-driven organization is essential because it forces employees out of their comfort zones. Teams and employees who have not had extensive exposure to data before will need to accept and adapt to new business strategies. It's also conceivable that new procedures and tools may lead to skills gaps that need to be filled by new positions or efficient training initiatives.

 

Even if it seems like you are in the dark about how to create a solid data strategy and make the most of the vast volumes of data at your disposal, you are not alone. It's crucial to invest in digital technologies, be adaptable to changing demands, and take your time to establish well-structured business procedures. Although changing corporate culture might be challenging, the evolution and innovation will improve your organization from the top down.