In today’s world, organizations are increasingly recognizing the importance of becoming datadriven, as it allows them to automate processes, make informed decisions, and promptly respond to critical events. However, as they embark on this journey, they often encounter challenges in aligning their data platforms with organizational goals In this blog post, we will delve into a fictional scenario where a company, driven by the desire to harness the power of data, faces obstacles in creating its data platform. We’ll explore the root causes of these issues and provide actionable steps to bridge the gap between an organization’s data strategy and its overarching goals. It is a situation that we have helped tackle many times at Aurai, allowing clients to get back on track building data platforms that deliver exactly what is needed.

 

The context

Let’s assume a company that has been selling service products for a couple of years. Due to their market expansion and stakeholder growth, they’ve chosen to partner with several third-party application suppliers for processes like human resources, finance and customer complaint handling. Due to the growing number of stakeholders, management has decided to focus on becoming datadriven. They’d like to see more process automation and be aware of important events as soon as possible in order to dedicate their employees’ precious time accordingly.

As it’s hard to hire a full data team with lots of seniority, management decided to begin working on an initial proof of concept with a less experienced team. The goal is to deliver a finance dashboard for management that can aid in their weekly finance meetings. It will save the company’s financial team lots of time as they don’t have to build weekly Excel reports anymore. Additionally, the thirdparty finance application in use by the company provides excellent integration with the cloud platform they decided on using.

After several weeks, the data team got the new data platform up and running, and the new finance dashboard has proved itself to be very useful. Management therefore decided on expanding the company’s data platform. HR indicated that a dashboard would greatly improve their performance, as boring and repetitive tasks could now be automated. Eager as the -still new- data team was, they took on the new challenge. The third-party application used by the HR team to manage their data turned out to be a bit harder to extract data from, but with a lot of experimenting, the team eventually made it happen.

Fast forward a year or two, and the data team is in a situation where a lot of data sources are being loaded into the data platform every day. Different business departments became aware of the new Finance and HR dashboards and began requesting dashboards for their own. As the data team gained experience, the ways in which the data was loaded into the platform also changed. The team experimented a lot and different employees worked on the platform.

At today’s early morning meeting, one team member mentioned his conversation with another employee at the coffee corner. It was a very urgent request concerning the application where customers can address complaints regarding the services delivered by the company. Management makes data privacy and security a top priority due to recent leaks covered in the media. The department that handles complaints needs to ensure that only specific employees are able to see the most sensitive data. The problem is, many employees have accounts for the thirdparty complaint handling application, and it’s hard to see who has certain authorizations. A dashboard displaying this data needs to be delivered next week

The coffee corner is a space for conversation and relaxation—not for addressing business requests. Photo by Crew on Unsplash

The person who initially built the pipelines to extract data from the complaint handling application to the company’s data platform had already left the team without any documentation in place. Upon further inspection, the implementation of complaint data in the data platform seems to be very messy overall, consisting of multiple approaches originating from ad-hoc requests over time. The team is almost certain that it will take a long time to link authorization data with the data already in place. Additionally, the sensitive data that management is concerned about is already visible in a large number of dashboards without any clear data traceability. The absence of proper documentation, combined with the chaos of multiple projects and ad-hoc requests added to the data platform over time, makes it impossible to complete the request on time

What happened?!

At Aurai, we have seen similar circumstances in multiple situations. An eager company and newly formed data team taking on the challenge to generate ‘impact’ and ‘value’ for a company committed to becoming data-driven.

The intention, such as at the above described company (from now on, ‘the company’) is always great. Initial insights are often gained quickly when working on a new data platform. However, be aware that these initial quick and easy gains are both the curse and blessing in the whole story. The company quickly began handling new requests from other business departments without any real processes in place to handle those request accordingly. The data platform essentially never abandoned being a proof of concept. It gave room for experimentation and priority management based on ‘the loudest person in the room’. This resulted in all kinds of different approaches and data streams entangled with each other in a quick but disorganized expansion of the data platform.

The main overarching cause for this to happen can most of the times be distilled into:

1) A disconnection between a company’s overall strategy and it’s data strategy.
2) A disconnection between the data platform team and other business units.

Ideally, after the success of the initial proof of concept, a data strategy was written. It addresses all of the crucial matters such as coding standards, the tooling to be used, the handling of business requests, and, most importantly, how the data platform aligns with the company’s overall strategy.

Imagine the company’s primary strategy is to ensure customer happiness by delivering exceptional service and addressing complaints with care and efficiency. When organizational and data strategies are aligned, it becomes unlikely that the company would begin to build a dashboard for HR immediately after the proof of concept. Instead, integrating the complaint-handling application into the new data platform would be a far wiser move. Additionally, well-designed data models and clear rules of engagement would greatly support the integration of customer complaint data into future projects, avoiding the current challenges caused by its fragmented platform and processes.

So what’s the fix?

The first and hardest step is to realize that a data platform is disconnected from organizational goals. This, of course, can present itself in different ways, but typical signs are:

• Apparently small requests take ages to implement.
• A data platform with a large amount of different approaches to achieve the same objective.
• A large amount of business requests waiting to be implemented, lacking adequate background information or prioritizing.
• Implemented business request without any sight of their actual use case or usage.
• A lack of communication regarding the data platform across all business units.

It’s challenging to navigate a data platform with numerous non-standardized pipelines and techniques, all converging toward the same objective. Photo by Tyler Lastovich on Unsplash

Next, the best step is to halt development work on your data platform. Clearly communicate this to all business units and other relevant stakeholders as some might be waiting for their requests to be handled. Ensure everyone understands why this decision has been made and knows that it’s for the better.

Go back to the drawing board! What exactly does management expect from the data platform to deliver? Buzzwords like ‘impact’ or ‘value’ are not enough here. What goals does the organization have and how can a data platform help to reach those? Struggling to fully translate your organizational strategy into a data strategy? Our team members specializing in data strategy and governance are able to aid you in the process of creating or adapting your data strategy. They specialize in translating between C-level and business teams’ wishes, organizational goals and technical requirements. Making sure business teams feel heard, and data teams know exactly what is expected. By incorporating data governance practices in your data data strategy, they’re able to safeguard consistency and uniformity within the data platform.

With your new data strategy in mind, begin identifying the key parts of your current data platform that need fixing and make sure they’re implemented correctly. If different tools are required, now is the perfect time to make those changes. Our IT-architects can be of great help here, by analyzing your data platform and identifying its weaknesses. They’ll provide the essential stepping stones your data team needs to progress steadily. By evaluating current tools and future requirements, they can help ensure a secure and scalable data platform. Do you need extra engineers to move quickly beyond the current state and focus on extracting value from your data platform again? We can bring various kinds of engineers to your team and deliver the exact man (or girl!) power that is needed.

We highly recommend laying stepping stones to celebrate successes and keeping track of progress. Photo by Jamie Street on Unsplash

Effective communication is crucial throughout the entire process—not only between the data team and management but also across all departments. Regularly refer back to your organizational and data strategies, adapting your data strategy as needed by implementing continuous feedback loops. Make sure your organization is informed about the anticipated timeline and the new ways of working in the future. Will their requests be handled differently? What is expected of everyone in terms of future collaboration? To support this process, having a product owner on the team can be a game-changer. They play a vital role in managing expectations across departments, prioritizing tasks effectively, and ensuring smooth communication. By taking on these responsibilities, a product owner enables other team members to focus on their core duties, which can significantly enhance development work.

Final thoughts

Building a modern data platform isn’t just about technology—it’s about strategy, governance, and fostering collaboration between data teams and business units. A disconnected platform leads to inefficiencies, compliance risks, and poor decision-making. By realigning your data strategy with organizational goals, implementing best practices, and fostering cross-functional communication, companies can future-proof their data platforms and unlock sustainable value.

At Aurai, we specialize in guiding organizations that face challenges. Whether you need data strategy consulting, technical architecture assessments, or skilled engineers to strengthen your team, we’re here to help.

Ready to transform your data platform?

If your data platform feels disconnected or is holding your business back, let’s talk. At Aurai, we help organizations realign their data strategies, optimize their platforms, and turn data into real business value.

Reach out to our Head of Data – Nik Papathanasiou, at nik@aurai.com or visit aurai.com to explore how we can help you take the next step toward a smarter, more effective data platform.