Ever since the data revolution, organizations of all types and sizes have enthusiastically bought into the boundless promise of data to streamline problem-solving and revolutionize innovation. It is estimated that the data analytics market will grow to $303.4 billion by 2030, at a staggering CAGR of 27.6%. The growth of the IoT market, rising demand for real-time analytics, the widespread buzz around the capabilities of Generative AI, and increasing focus on customer experience are key factors driving this growth.

However, despite the significance of data analytics, many struggle to realize the true potential of data, due to the many inherent challenges within their businesses. Not only do these challenges impact the quality and accuracy of business decisions but they also impact employee morale, market standing, business reputation, and customer loyalty.

From siloed departments to on-premises systems, here are the top 3 obstacles that impede effective business decision-making and the possible solutions to overcome each of them:

Siloed Departments

Large organizations often have multiple teams needing access to critical insights to drive the right outcomes. However, very often they rely on standalone tools and multiple databases to unearth insights and turn them into action.

1. Information, when stored in distinct systems, leads to poor transparency and collaboration across the organization, while also resulting in incomplete or biased decisions.

2. Different departments working independently on similar projects lead to unnecessary duplication of effort, wasted resources, and conflicting priorities.

3. Taking a department-wise approach to decision-making may lead to missed opportunities and reduced agility as teams wait for inputs and approvals from other departments.

4. Poor cross-departmental alignment also leads to inconsistent strategies and goals which impact the achievement of broader organizational objectives.

5. When decision-making is restricted to departments, there is also the probability of disjointed customer experiences.

A centralized approach to business decision-making can lead to higher efficiency, productivity, and results. Individual teams and tools, when integrated, allow for better collaboration, visibility, and transparency. For instance, a microservices-first architecture can expose digital services and applications through APIs and allow for seamless interconnectivity between siloed departments. Such integration can empower teams to work together to drive larger business objectives while also meeting individual goals.

Unstructured Data

Businesses today collect and store humongous volumes of data daily. A large percentage of this data is unstructured, and a lot of it is also irrelevant, unimportant, and of no use.

1. The sheer volume of data makes it impossible for IT teams to run analytics algorithms on these datasets.

2. Large and complex data sets are difficult to store, manage, and share and often drain storage and processing resources.

3. Decision-makers have a tough time extracting meaningful insights from these complex and non-uniform datasets.

4. Inaccuracies and inconsistencies in this data demand substantial time in cleaning and preparing the data for analysis.

5. Unstructured data also tends to raise concerns about privacy and security, requiring organizations to implement appropriate measures to protect it from unauthorized access and breaches.

To overcome the challenges brought about the unstructured data, organizations can explore the many benefits of Generative AI. Advanced GenAI models can automatically cleanse, sort, and prioritize data for analytics and empower businesses with the data they need to streamline decision-making. Such automation brought by GenAI can also help in discerning sentiments and emotions and provide valuable insights into customer preferences, market trends, and employee perception.

Scalability Issues

The presence of siloed departments and systems also impacts data accessibility in many ways. Critical business and customer data, when stored in rigid on-premises systems, are too difficult to access, manage, and scale.

1. On-premises data analytics systems are incapable of handling growing volumes of volatile data.

2. Teams have a tough time scaling surging unstructured and semi-structured data and which involves substantial costs and lead times.

3. Setting up and maintaining on-premises analytics infrastructure is an extremely costly affair, requiring investments in servers, storage systems, networking equipment, and other hardware components.

4. Traditional analytics platforms also lack the agility and flexibility to respond to changing demands.

5. Organizations must ensure the physical security of data center facilities via access controls, surveillance systems, and environmental controls.

Cloud data analytics offers a great opportunity for organizations to overcome data access and scalability challenges brought about by on-premises systems. Offering seamless, anytime, anywhere access to intelligent insights, cloud analytics improves organizations’ ability to scale their analytics efforts, thus improving business agility and resilience.

Build a Data-first Culture with Recode Solutions

In today’s era of digital transformation, data has become the new fuel. As the volume of unstructured data grows, organizations need to change their approach to business decision-making. They need to invest in scalable infrastructure to handle increasing storage and processing demands while also streamlining storage, access, and management.

At Recode Solutions, we take a software-first approach to overcoming the challenges brought about by siloed departments and on-premises systems. Using the power of modern technology innovations like Generative AI, automation, and cloud, we help businesses make sense of growing volumes of data and steer their business in the right direction.

As we revamp your analytics journey, you can focus on critical priorities and drive continued business success. Looking to overcome these common obstacles? Contact us today and allow us to build a data-first culture across your organization!