Fear and Loathing in Data Analytics

Fear and Loathing in Data Analytics

By Stiliyan Neychev

December 15, 2023

We’ve talked to our clients, Fortune 500 companies and large enterprises, about the fears of data, being stuck in reporting, and the never-ending battle between IT and Business.  For obvious reasons, there are no names included, but if you have any questions regarding the article, email us

The reality of the data analytics landscape in the corporate world 

Large enterprises in all industries are stuck in business as usual. That’s the general theme in those organizations’ data analytics spaces. They talk a lot about data, how it is essential, and how they make data-driven decisions. The reality though is different. 

“These companies have gone so bureaucratic that the division between IT and Business is even bigger than it was when they were deploying data centers and doing network-type deployments in the 90s. Now they’ve moved those deployments to the cloud, but the division between what the business needs and what the IT can deliver is still a big gap.” 

Sales Director

And one of the reasons is the skill set. 

Most companies have a skewed view of AI, self-service, etc. They all say data is critical to the business in terms of making informed decisions. At the same time, a $30 billion company says, “we don’t need real-time” when they have supply chain disruptions. And these companies are manufacturers and technology leaders which are considered data-first companies. 

In a similar scenario, a $9 billion logistics company says, “reporting is good enough – we don’t need advanced analytics”. And they have thousands of trucks that they have to manage every day. Reporting is not analytics, and data visualization is not self-service. This is the first thing that these companies need to understand. The more they realize what data analytics is and what it can do, the bigger their opportunity for better performance is. 

“What I am hearing is a complete lack of understanding of what analytics is. I almost had to call it advanced analytics for people to understand, that you are not doing analytics, you are doing reporting. That’s not good enough.” 

Senior Manager, Analytics & Insights 

What is good enough? Let’s start by understanding what analytics can do. 

There is a global lack of understanding of what analytics is and how to gain knowledge from data. Major companies use Google Analytics as their data analytics. Nothing wrong with Google, but you cannot connect the dots between your marketing and financial data, get to the bottom of the increased employee attrition or analyze trends in GA, even if it is the almighty GA4. 

Is Big Data and Advanced Analytics too complex to handle

And then there is data literacy. And it’s missing. Or more precisely, data literacy when it comes to technology is missing. Everyone talks about AI, but no one can tell the difference between AI and ML. Big BI tools like Qlik, Tableau, and PowerBI are talking about machine learning but most of their clients don’t use it. And the companies that use those capabilities have Data Science departments that spin the wheels so that other departments do not have to bother with data literacy.  

But how many of the big enterprises need to start building Data Science teams to improve their data capabilities? Probably none. They first need to get the basics straight and go just one step further than reporting. 

Are Big Data and Advanced Analytics too complex to handle for most companies? 

“Big companies make it too complex. That’s why Hadoop took a dive. Mostly, companies were dumping everything into it and could not make sense of what’s what.” 

Head of Business Intelligence 

When you cannot find where the data is coming from, there is hardly anything useful that you can use that data for. That’s why Snowflake is going up. It allows you to structure the data and know where it is. It provides an understanding of where the data came from, lineage, etc., and makes seamless connections between data sources.  

The market just needs to be willing to realize that such solutions are right there in front of them. Even if it sounds too complex to handle in the beginning, the vast majority of those companies who use it reported high adoption rates. 

Knowing where the data is and where it’s coming from is vital to data-driven decision-making. For this to happen, your teams need to see the data, understand it, and be able to manipulate it. Not enough value is associated with enabling more employees to get access to the data so that they can get used to working with it.   

Self-service, for example, allows real-time collaboration on the same dashboard for different users. Those who haven’t tried self-service say it is complicated. Those who started actively using it in collaboration with their team say that this is how most valuable insights are discovered.  

Qlik Self Service

NLP is another example of a complex concept that, in fact, makes working with data easier. You don’t need to figure out where the data is; all you need is to connect to the tool’s NLP voice assistant and say something like, “show me the sales for widget X and region Z”. It automatically pulls up the data, you don’t have to know where that particular model, or answer, or data source is. It gives you the visualization right away. 

And on the other hand, there is a self-service functionality called Alerting. Whenever a trend is going below or above a certain threshold, you will be instantly alerted about it and can take action. This is called making data proactive. For some, this may sound like a complex concept that needs setting up, etc. In fact, this is exactly the thing that makes your daily work easier.  

Complex or not, most companies just don’t know these capabilities are there for them to make their lives easier. They often say they are not seeing the value of analytics, but really they don’t want to make the effort of understanding what’s out there and what it can do for them.  

What are businesses afraid of? 

“What we see, on both the data integration side and on the data analytics side, is that you really need someone who is willing to risk their political clout.”  

Business Architecture Team Manager 

Someone in the company needs to say, “Hey, there is a better way, and I know how to do it. Let’s do it.” It can be someone from the business side or the IT side, but they need to make the first step. Most IT departments in our world don’t have the relationship with the Business to be willing to ask and to be able to talk about why they need money. They are more afraid, and that is a cultural thing.  

Throughout the time, big corporations and all of us in them created a culture in IT that doesn’t want to go and ask for money. It is much more acceptable to just use the set budget and not cause “inconveniences.” And it is a strong barrier to the development of a company in general, not just in terms of analytics. 

Another thing that stops businesses from embracing analytics is that there is a lack of people out there who have knowledge across BI, data integration, data analytics, data warehouse, and data lake. And when you get a BI tool, there isn’t any one person who would know it inside out. And honestly, there shouldn’t be. Or at least, you do not necessarily need to combine everything in one person. That is why partners and vendors exist, who have teams specializing in these tools. 

why business intelligence is so important

 If you look at the very high level, there are two parts to managing a BI tool. There is an analytics front-end part – self-service, etc. And then there is the data pipeline. Then the 3rd separate part would be where you are going to land that data for analytics and stitch it together. And for all of this, you need qualified people. 

“In the pipeline part, people are still doing ETL. And I don’t fully understand why. I do understand that there are heavy transformations where maybe ETL needs to be involved. But the type of software that is out there automates that.”  

Senior Manager, Commercial Applications 

Often in big corporations, there are existing systems which are groups of ETL development that some Director or Senior Manager built up over time. And they are defending that work by not going for a more automated platform and not looking for other alternative software and capabilities outside of their own ETL work. Often, organizations are afraid of change and analytics because there are people in those organizations who think their work will become meaningless because of it.  

For a company like that, it takes someone who sticks their neck out and says, “that’s not the way to do it”, and they have the knowledge to stand up to that. 

Is IT holding back the business? 

Generally, IT is holding back business. This is a theme. That’s not anything new, it’s been done for a long time. Lack of communication between the Business and IT is a big part of it but there are other factors. 

One example is the CTO or CIO or any C-level technical position’s average time of employment. The average CIO tenure is currently at 4 years and 8 months.  

median cio tenure in analytics industry

It is a relatively high turnover for such a position. And it is likely happening because the CIOs do not listen enough to the Business and do not collaborate as much as they should with the Business and partners. Thus, the results aren’t as good as expected and the performance of the team goes down. 

A different example is companies that say, “we are data-driven”. In this case, more often than not the IT department is “doing the best they can”, which usually is the bare minimum. Or they are doing the best they can with the resources they have. And the Business thinks that is the best that is out there, even if they need different functionalities.  

“I know a big entertainment company that says, “we’re data-centric”. And what they use today is in their minds good enough. They use data in a certain way that helps them make informed decisions. But are they taking full advantage of AI capability? ML capability? Are they seeing all the data? No, they are not. They are almost like, “this is the best we can do.”  

Business Analysis Manager 

Generally, it takes an IT person who wants to hear and understand what business value is to make a step towards analytics. You see success when IT is integrated well and works well with Business. For this to happen, the Business has to push them and explain their needs, but IT has to be receptive to that push, and then they can collaborate. That’s where success happens.  

More and more people start seeing the opportunities that IT-Business collaboration provides.  Usually, it would be a group of motivated people with an idea, that understand that they need to look outside the box to see what else is out there. 

Improving the IT and Business collaboration 

Let’s go to my experience back at Oracle. Say there is an issue with a CRM application. I would conduct a consulting engagement, where I come, as a service provider, and bring IT and Business together in one room. I would lead the conversation to identify the current issue, and then together we would identify the data and architecture. From there, I would give recommendations.” 

Director of Analytics 

What you would see in that engagement is bringing business and the IT group together and walking through what one person or group sees the issue is and then the other. Documenting how things work: the process, the people, the technology – is important. Usually, you’ll notice that these 2 groups aren’t in the room with each other very often. 

For this process to work, you need to understand the business challenges. What are you not seeing and not getting today? From a supply chain perspective, are you able to see in real-time where things are in your logistics pipeline? In HR, do you see retention, how training is affecting it, etc.?  

There are many hypotheses that you can test, for which both Business and IT need to be involved. Make sure you start small in the area where you have enough data. 

how it and business collaborate

And when you know the challenge that you want to solve, try to bring these two groups together to identify the problem in their communication. Either group has to be open to working with you. Then the other group needs to be pulled in. If the Business wants the change and is ready to collaborate, then they have to pull the IT in and vice versa.  

Where I see the most traction is where the company already has a BI tool, and there is a knowledge leader in that area who understands analytics and the general landscape of the BI tools. You need leaders who have a strong enough voice so that the teams would listen to them.” 

Senior Manager, Analytics & Insights

Bringing the company to a better place data-wise is really about bringing the Business and IT together. And sometimes you can’t just do it. It takes organizational change, new policies, data governance, etc. But the results you can achieve when your company’s departments are working in sync are remarkable. 

Seeing ROIs on data analytics

Let’s consider the definition of advanced analytics to be analytics beyond reporting and visualization, for now. This means enabling the business to see all your data and drill into it to get valuable insights.  

Businesses that are able to deploy analytics solutions correctly and maintain them to see all their data and democratize it –see ROIs immediately (in 3 to 6 months).  

When you make straight-off choices of tools, partners, and integrations, and are able to manage the pipeline, you will see results. But if your ongoing data management process is not working properly, your results will suffer. 

Some companies think they need to do everything themselves. No, that’s not how it works. Focus on time to value. It is important to pick a platform that suits your needs and capabilities and not just go with the industry flow.  

Take Salesforce, for example. Do you know how many Salesforce implementations take years and millions of dollars?  

Don’t overcomplicate to get ROIs. 

You want advanced analytics. Choose a platform, reasonably. Make sure you deploy it correctly. Make sure you understand the business KPIs. Manage it and create a process that is optimal for your company. This is how you get the best time to value. 

What can help quicken analytics adoption? 

Having organization-wide access to BI platforms helps with getting the ROI quicker and makes it last. Democratizing the data to more stakeholders while governing it (you don’t want anyone to be able to see any data, especially that they don’t need to see) most certainly leads to better adoption. Business value goes up, and the retention rate likely goes up, because people can see the value of their work almost immediately. And that brings the ROIs. 

If you fancy a formula for success, it would be something along the lines of:

collaborate between the departments + listen to the business +
understand business challenges = ROIs.

When your teams collaboratively look for solutions to business challenges, the magic happens. 

Set up a structure to validate the challenge. Come up with a Proof-of-Concept project and choose the right partner to deploy and manage the analytics. It will be a tremendous help to you, especially in the beginning. 

Is analytics the Holy Grail of business success? 

“I don’t see how it wouldn’t be. How do you get an understanding of how your finance, supply chain, inventory, marketing, sales, etc. teams are performing? How do you manage a business without having analytics? It’s impossible.” 

Sales Director 

There are many companies that only do reporting and think it is enough. There are fewer companies that understand the value of real-time analytics and make the first steps towards a data-driven culture. And there are even fewer companies that are truly data-driven. 

No matter which group you belong to at the moment, there are always ways to improve the data analytics landscape in your organization. From choosing the right tool to putting IT and Business in the same room to discovering what AI and ML can do for you and your business. 

Embrace the chance and choose the right partners to do so. And the ROIs will come.