Episode #5 | Top 5 Problems Businesses Face in Data Analytics

Here are 5 key takeaways from the podcast:

1. Lack of a Clear Analytics Plan:
   Companies often dive into data analytics without a clear roadmap, leading to wasted resources and ineffective decision-making.

2. Data Silos:
   When data is fragmented across different systems, it’s difficult to get a unified view, which hinders strategic decision-making.

3. Trust in Data:
   Without trust in the accuracy and consistency of data, businesses can’t confidently make data-driven decisions, leading to hesitation and confusion.

4. Scattered Reports:
   Inconsistent data across different reports can cause confusion. Aligning and blending data from various sources is crucial for accurate insights.

5. Random Decision-Making:
   Without a structured data approach, businesses often resort to guesswork. Implementing a data-driven system helps shift from random actions to informed strategies.

Vadym:
Hey everyone! Welcome back to The Data Crunch Podcast. I’m Vadym, Growth Marketing Manager here at OWOX. Today, we’re talking about something that’s on every data-driven company’s mind: the big challenges of data analytics and, more importantly, how to tackle them. 

I’m here with Ievgen, our Head of Marketing, to walk us through the top issues companies face and a roadmap to solve them. Hey, Ievgen! Ready to dive into the world of data?

Ievgen:
Hey Vadym! Absolutely, let’s get into it. There are a lot of companies out there sitting on a goldmine of data but struggling to actually use it. It’s exciting to explore what’s getting in the way and how to get past those blockers.

Vadym:
Totally! So, let’s kick things off. What’s the first big challenge companies face when dealing with data analytics?

Ievgen:
Alright, first up is something that sounds simple but is crucial—a clear analytics plan, a roadmap. A lot of businesses dive into data without a structured plan. They want to get some reports, but they have no idea what they want to achieve with them. They have no idea what to measure, or what to optimize. 

Imagine it like jumping into a game without knowing the rules, objectives, or even the point of the game!
Sounds tricky, right?  That's how a lot of businesses feel about data …
They're overwhelmed with tons of information - from how folks are clicking around their website to the nitty-gritty of the sales metrics.
They’ve got all this data, but without a plan, it’s just a sea of numbers. Disconnected numbers. You can’t make any bold decisions with raw numbers or with some charts.
So starting analytics without the Plan can lead businesses to chase trends or buzzwords that don’t align with their actual goals.
Like looking at the spikes at the website traffic which leads to nowhere.

Vadym:
That makes so much sense. So without a plan, it’s easy for businesses to get caught up in whatever’s trending, right? Like, they might focus on metrics that don’t actually drive results for them.

Ievgen:
Exactly! With a roadmap, you know what are the business goals.
What are the milestones to get there - like specific data points to collect, specific metrics to measure, because you don’t need to measure everything.
As well as the list of very detailed questions you need to answer to achieve those goals… Which data points, which areas of business to focus on.
Data is massive… and it’s easy to get lost.
But once you've got that, things start making a lot more sense, and you can really level up your business game quickly.

Vadym:
Love the analogy. Okay, what’s challenge number two?

Ievgen:
Challenge number two is data silos.
Picture this—each team has their own set of data in it’s own place or system.
Maybe sales data is over here, social media stats over there, and website metrics somewhere else.
It’s like each piece of data lives in its own world, making it really hard to get a full picture of what’s going on within the business.
For example, How this ad is driving this specific sale happened 4 months after it was viewed.
Without a way to connect this data, companies end up with pieces of the puzzle instead of the whole picture.
Or another great example. If you just look at the reports from the advertising platforms - you’ll get more total sales than you actually have. Because each of those tracking pixels works differently, independently of each other and more importantly, you;re not the one driving that tracking behavior. 

Vadym:
Yeah, that’s a common issue. When data is siloed, it’s tough to get a single, reliable source of truth. It sounds like this is where a good data analyst comes into play?

Ievgen:
Definitely. A data analyst can help bring these pieces together, but it also takes the right tools and a commitment from the team to unify that data. To then use those unified data.
Otherwise, you’re just stuck in a loop of fragmented insights.
So yes, without a data analyst knowing SQL, it’s hard to handle all that,
But nevertheless it’s a team work, not just the data analyst himself connecting the dots.
It’s a team’s commitment to change… so business can grow. 

Vadym:
Makes sense. Alright, what’s challenge number three?

Ievgen:
So it’s connected to the previous one we’ve just discussed.
Challenge three is all about trust.
If the people using the data don’t trust its accuracy, they’ll hesitate to rely on it. It’s like trying to build a house on quicksand. The shaky foundation of mistrust. Without confidence in the data, bold decisions just aren’t possible. And when data is siloed and inconsistent, trust really takes a hit. Businesses end up guessing their insights, and it creates this cycle of hesitation and confusion. This leads nowhere quickly

Vadym:
Yeah, that’d be tough. If you don’t trust the data, you’re not going to rely on it, so it’s almost like having no data at all.

Ievgen:
Exactly. Trust is everything in data. Especially when business becomes large. When teams know the data is reliable, they can use it with confidence and start making those data-driven moves.
Because they still have to make those decisions themselves. Why not making the data-informed?

Vadym:
Alright, let’s move on. What’s the fourth challenge companies face?

Ievgen:
Challenge four is scattered reports.
Imagine you’ve got a sales report from your CRM system, a website report from Google Analytics, and maybe even a financial report from Quickbooks or whatever tool.
They’re all measuring the same things, but with different numbers.
It’s frustrating because each report might be technically accurate, but when they don’t align, it’s just confusing.
If the data isn’t blended, it’s almost useless because you’re left questioning which numbers to believe.

Vadym:
That’s a good point. It’s one thing to have data, but if it’s inconsistent across reports, it’s hard to act on any of it. So blending data would help here?

Ievgen:
Absolutely! Blending data is key.
When everything’s aligned and telling the same story, decision-making becomes so much easier and faster.

Vadym:
I get it. I understand how to blend different pieces of data. How to make sure all of the data pieces are alligned?

Ievgen:
That’s where business needs to step away from the traditional one or two data sources reports. Like you know all of those tools that advertise to bring all of your data into spreadsheets. Facebook ads here on one tab, google analytics data on another tab, quickbooks here, hubsport there, stripe in a separate document, etc.
And then you go and try to VLOOKUP from one sheet to another.
That’s the quickest pass to scattered reports.
The good way here would be to get all of the data into a warehouse. Google BigQuery, Amazon Redshift, Snowflake.
Whatever one you chose. They all are great.
And you model your data inside it. Using SQL. Nobody yet developed a better way to speak to data than SQL.
When I say model - it’s about connecting the dots between your metrics, between your objects that exist in the real world like orders, customers, sessions on the website, products.
Making all that tables and keys to connect those tables.
And then using this data model to build all of the reports within organization.
You can do that in spreadsheets, bi tools, anywhere. 

Vadym:
Alright, let’s wrap up with challenge five. What’s the last big hurdle?

Ievgen:
The fifth issue is random decision-making.
Without a solid analytics system, businesses often resort to “throwing things at the wall” to see what sticks.
It’s like, “Why’s our conversion rate down this month? Should we change the homepage banner, update the email campaign, or maybe run a webinar?” There’s no data-driven direction—it’s just guesswork. And the sad part is, they could be using data to guide these choices but are instead just guessing.

Vadym:
Wow, yeah, that sounds exhausting. It’s like spinning in circles without making real progress. So I guess the goal is to shift from guesswork to data-driven decisions, right?

Ievgen:
Exactly. With the right data structure and the processes in place, you’re not just guessing. You’re making informed decisions based on what’s actually happening.
It’s a complete shift from random actions to intentional strategies.

Vadym:
Alright, so those are the five big challenges. Now let’s talk solutions. How can companies start tackling these issues?

Ievgen:
Good question! It all comes down to three main things: you, a plan, and tools. First, it starts with you—or rather, your commitment to change and making data a priority in decision-making.
Then, you need a clear plan, which acts like your roadmap. Without it, it’s like setting out on a road trip with no destination in mind.
Lastly, you need the right tools—data storage, visualization, and a data analyst to handle your data properly. 

Vadym:
So it sounds like companies need to get really clear on their roadmap first, then focus on getting the right tech in place?

Ievgen:
Sure. And we actually have a complete 12-step Data Analytics Roadmap that we’ve developed after working with over 160,000 users.
It’s designed to help businesses build a structured analytics system, step by step.

Vadym:
Alright, I’m intrigued! Can you walk us through that roadmap?

Ievgen:
Sure! So, the roadmap has four main stages: Plan, Collect, Prepare, and Deliver.

In Plan, you’re setting out what you actually want to achieve with your data. This means defining clear goals, picking the right metrics, and figuring out who’s in charge of what. It’s all about laying the groundwork, so everyone’s on the same page.

Then, Collect. This step is all about gathering the data you need and making sure it’s accurate and complete—no missing pieces. You want the relevant data to fit into the bigger picture.

Vadym:
Ok, I see. So at first, we Plan what we want to get, and then we Collect the data. What’s the next stage?

Ievgen:
Next up is Prepare. Here, we’re taking that raw data and getting it organized. We’re cleaning it, merging it, and making sure everything lines up. Think of it like setting the stage so that your data actually makes sense and is easy to work with. Creating clear tables aligned with business objects that exist in real life.

Finally, we have Deliver. This is the exciting part where all that data turns into real, actionable insights. It’s not enough to just create a report.
Instead of just looking at numbers, decision-makers should be using those insights to drive growth and make decisions that push the business forward.

Vadym:
I love that it’s all laid out like that! And I can see how following these stages would make it way easier to keep data organized and reliable. 

If you’re ready to dive deeper into these four stages—Plan, Collect, Prepare, and Deliver—don’t miss our dedicated videos on each stage on our YouTube channel! Subscribe now and start exploring actionable tips to optimize your data processes.

Ievgen:
That’s exactly the goal. By following this roadmap, businesses can avoid the common pitfalls we discussed and actually start using data to drive growth.

Vadym:
Great stuff! So, to sum it all up: data doesn’t have to be overwhelming. With the right roadmap and tools, it can actually become your secret weapon for growth, right?

Ievgen:
Absolutely! Data isn’t just numbers; it’s the insights that lead to progress. With a structured approach, companies can go from reactive to proactive—making decisions that actually move the business forward.

Vadym:
Perfect. Thanks for sharing this with us, Ievgen!

And to everyone listening, if you’re ready to get your data working for you, check out OWOX BI and start your free trial at owox.com.

Subscribe to The Data Crunch Podcast for more insights on how to leverage data in your business. I hope to see you in our future episodes.Ievgen:
Thanks, Vadym! And thanks, everyone, for tuning in. Remember, data should work for you, not the other way around. See you in the next episode!