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Without realizing it, your company can suffer from inadequate or inaccessible data.
Research suggests that most companies do. According to the 2023 Zendesk Customer Experience Trends Report, only 22 percent of business leaders report that their teams share data well.
When companies don’t effectively share data between teams, the result is data silos. Data stays in one place where other teams can’t access and utilize it, resulting in everything from poor product development and customer experiences to increased costs and decreased productivity due to re-work.
To stop silos in their tracks, businesses need to employ data integration, the process of combining data from multiple sources to create a unified data set capable of utilization throughout your organization.
Data integration efforts come with a unique set of challenges best faced through collaboration, which is one of the central tenets of the agile methodology. Agile refers to a project management approach born out of the idea that software development should focus on individuals and interactions for continuous improvement.
With data integration being such a crucial and expansive project, breaking it down into right-sized tasks that your teams can achieve is vital. Which begs the question — how do you go about finding the right size?
How to Right-Size Data Integration Tasks: Story Points
Data integration is a hefty task, especially if your company has not prioritized data organization and sharing in the past. It’s better to divide this large, overarching mission into smaller, right-sized tasks to encourage your teams throughout the data integration process.
This is where the story points method comes in, which outlines how to make work estimations beyond just simple time approximations.
When assigning a task, you may think it’ll take two hours. However, what takes a senior engineer two hours may take a more junior worker significantly longer.
Inaccurate work estimations can create inaccurate timelines, making projects take longer and affecting your overall data integration workflow. They can also be discouraging for workers, who may feel like they’re falling behind or not reaching the goals you set in place for them.
Story points are more data-driven and create more achievable goals. For each task, you’ll assign story points, which tell workers how much effort they’ll need to accomplish the goal, as opposed to simply how much time. Many teams base story points on the Fibonacci sequence, where bigger numbers indicate more challenging tasks. This works well because the way the numbers scale aligns with how effort as well as unpredictability scales with larger and/or more challenging tasks.
Switching to story points can improve collaboration and remove skill bias, creating a more engaged team, which is ultimately a boon to your whole company. Gallup’s research found that involved employees result in higher profitability, productivity, and customer loyalty. It also leads to lower rates of absenteeism, turnover, and instances of product defects.
When you first begin to implement story points, you won’t yet have the complete picture of what your teams can accomplish to properly create the right-sized tasks. Rest assured that, in time, you’ll be able to document your struggles and successes to better score which tasks need what number of points.
Learn how to easily integrate story points into your agile estimation workflow here.
Optimize Data Integration by Maximizing Data Accessibility
Now that you have the strategy to right-size data integration projects, it’s time to focus on the data itself. The data you’re working with needs to be accessible, pliable, and available in a clean and usable format.
Otherwise, it’s going to be difficult to integrate across your business systems in any reasonable amount of time. In addition, why bother going through the trouble of getting it all plugged in if it’s barely useful to the teams that need it most?
This is where data-as-a-service (DaaS) comes in.
DaaS refers to storing data in a cloud-based system that allows users to access essential information through various platform and application integration. Cloud-based systems can help knock down silos by creating pathways between teams, allowing one team’s data to reach another team for their usage.
DaaS tools prevent data silos and allow for better data-driven decisions throughout the company. Modern DaaS platforms don’t just democratize data, they also help clean it, validate it, manage it, and run analytics on it so you know exactly what you have access to.
DaaS is critical to large and data-dependent companies because incomplete or inaccurate data leads to poor decision-making. Insufficient data results in companies losing an average of $15 million per year, according to a Gartner survey.
With DaaS, teams can rely on data that they know is complete and true, resulting in better business decisions that can affect everything from customer experience to profit margins.
Here’s to Staying Agile in Your Data Integration
Through the informed right-sizing of agile dev tasks and the DaaS systems that disperse essential data, your data integration methods can create a workplace that’s more engaged, productive, and profitable.
Think of your data as currency — especially since data-driven decision-making ties so closely with higher profits. You should protect your wealth of data, making it accessible to the right people and usable for the workflows that power your business.
Follow this guide to create a cycle of effective data management and integration that’s just as agile and constructive as the rest of your development cycles.
