Data, Business and Communication Gaps

Have you ever been a part of a data team or a business team which relies heavily on data? Then you would’ve had communication issues… you know what I am talking about.

I’ve also been through this situation one too many times, where the data and business teams are not on the same page. This could mean a team is using a separate external platform to track analytics, different from your warehouse, or the data team modifies or deletes a dashboard they thought was no longer relevant to the business.

Simple processes are made much harder and longer than they need to be just with a disconnect between business and data teams. Things that should take weeks to complete end up taking months because of the lack of proper communication. Or, even worse, there are?too many?conversations where thoughts are being repeated because objectives are not properly aligned.

Well, this is a difficult problem to solve but not an impossible one. Keep reading if you want to learn how to bridge the communication gap between data and business teams.

What a disconnect looks like

There are different ways in which disconnects are manifested between business and data teams. As an Analytics Product Manager here are some of the most common ones I’ve experienced.

“Sources of truth”

Data teams most important goal within a business is to identify one source of truth for the data. This ensures numbers across multiple teams all match up. Further, it makes it easy to rely on data rather than questioning every single conflicting source.

However, this is a hard goal to reach when your organization doesn’t have a mature data culture. Let’s understand by an example. Imagine we are ingesting data from LinkedIn, Facebook, and Google directly into Snowflake while other marketing campaign data is coming from Excel Sheets. However, there are also some external platforms and systems that are being used to make decisions, but the data from these platforms never even makes it to the data warehouse.

This occurs because the data team doesn't fully understand how the business teams are looking for answers in the data available to them in different ways, as for business teams tracking things in google sheet makes more sense. However, in the data team's perspective this google sheet approach is very much prone to human errors. It's neither automated nor a solution that can be relied upon.

If there are?manual processes?being used within your organization, such as manual entry sheets and emails throwing around numbers, you need to look for a data platform that centralizes your data sources and bridges the gap between teams.

Major process changes and communication

Often seen business and data teams don’t realize when they have to be involved in a conversation.

For example, we always observe a false alert in scenarios where the marketing team disables all advertising campaigns across platforms and doesn’t notify the data team. Another scenario is when a business team wants to launch a product without any thought of the data that needs to be collected about the launch. It’s hard to realize who needs to be involved in which processes when team are siloed.

It’s important for both the data and business teams to know how one’s action affects the other. Data teams might not realize that changing key data models or altering the data ingestion pipeline could change how metrics are tracked. Business teams might not realize that changing any type of data source could break production models and cause false alerts.

Hence teams need to effectively communicate what they are working on and how this could affect each other's responsibilities.

Goals & priorities that are misaligned

Business and data teams are often misaligned on their priorities and future goals.

Misalignment runs deep in an organization. For example, one may consider a certain initiative as a top priority, while it might be something else for the other team. This often stems from a deeper communication issue where teams don’t properly understand the value of each others work. If this is the case, teams will never consider other people’s goals as important as their own.

Always frame or reframe goals to value work of all stakeholders. For example, business teams may want their ad-hoc requests to be prioritized over long-term efforts, like data quality initiatives. However, when performing ad-hoc requests, it becomes hard to prioritize foundational efforts such as moving away from spreadsheets, rebuilding data models, and standardizing columns.

In this case there is always competing priorities if the value proposition & goals aren’t reframed in a way that is valuable for all stakeholders involved.

Ways to bridge the disconnect

In my experience, data and business teams’ disconnect can be solved if the organizations communication is clear and you set up systems to prepare for success.

My top tips for working out your communication gaps with the teams.

As a data team always present the value of your work.

The data team should always present its value of work to the business team in an understandable way.

Business teams will have a much easier time getting on board with initiatives when they know how it directly or indirectly affects them. For example, saying you are focusing on “data quality initiatives”, will mean nothing to other teams. Instead, let them know you are implementing tools and checks that will allow you to find data issues at the source so that they don’t create downtime in the dashboards they use every day. This provides value to them because now they will no longer have to contact the data team when a dashboard is down or wait for it to be fixed to move forward with their goals.

A good way to communicate with business teams is to explain the issues occurring?now?and how the work you want to do will prevent them from happening in the future. This helps business teams understand the immediate impact that can come from the data team’s work outside of ad-hoc requests.

Always showcase accomplishments and educate teams on your data stack by creating a communication channel. I highly recommend creating a "# Inside insights" chat channel to publish highlights. All my teams implement this practice, and it helped us gain a lot of appreciation and understanding for our hard work.

Create systems that allow ease in communication

You need to put systems in place to make cross-team communication easy.

Always think about how to bridge the communication gap. Teams need to know exactly where to look and what to do when they need something from one another.

I recommend creating an intake form for business teams to fill out when they have an ad-hoc request. Have a pre-set form with very specific questions so we can get all the information we need to do our jobs without constant back-and-forth communication. It also forces business users to think twice about what they are asking for, prioritizing only the most important requests.

One way my team has bridged the communication gap by sending monthly release emails. In each of these emails, we list our major accomplishments from the previous month and frame the value from a business perspective. We also include what we are working on in the upcoming sprints, so teams know what to expect in that time frame. This communicates our long-term goals to outside teams and how they are affecting the rest of the business in a positive way.

Lastly, I highly recommend creating an event calendar, so your data and marketing teams are always on the same page. A calendar creates clear communication without having to go back and forth. This will make it easy for the data engineer to change data quality checks depending on the data sources being used and disabled. It will also act as a great cross-reference in the case of receiving an alert that data volume is low & will allow try to identify the cause of an issue relating an calendar event.

Adopt to the SCRUM framework

SCRUM framework works !! it will help you minimize ad-hoc requests and prioritize foundational data work, like building models, creating dashboards, and increasing data quality.

One of the biggest component of SCRUM is assigning specific tasks to certain sprints?before?they begin. This means we cannot throw a new, urgent task at you while in the middle of a sprint. They must wait until the sprint is over to then assess its priority compared to other tasks from the backlog.

I have seen this system forces business teams to think weeks and months ahead about their future requests for the data team. Most times, they end up solving the issue on their own or realizing that it’s actually not that important. They are forced to respect the timeframe that the data team is working on and consider if their ad-hoc request really is a priority.?

This ends up helping both teams because the scope of work is properly assessed before jumping right into the task, leading to less burnout from the data team.

Conclusion

Communication between business and data teams will never be perfect. There will always be some sort of disconnect, especially each of you are focused on your goals, trying to find success as an organization. Just make sure you are continuously moving in the right direction and improving how you work with one another to bridge your communication gaps.

Business and data teams working together smoothly impacts your organization as a whole. It will save valuable time & allows people to do the work that really matters to them. It will produce more reliable insights, helping the business grow to new heights. And, it will make room for you to build on all that you’ve already accomplished, allowing you to achieve even more amazing results.

Adopting a collaborative data platform?as your single source of truth is a great start. When business teams ask you to add a new data source to the warehouse, that’s a sign that you are doing something right. And when business users show interest in data education, you have something special happening.

So, make sure you put in the effort to make this ideal scenario your reality.