Cloud Migration

The tl;dr on Achieving Enterprise Intelligence in The Cloud

May 14, 2024
Lindsey Norman

We’re living in a data-driven era, one where businesses are overloaded with information–from customer interactions and market trends to internal operations and performance metrics. Research shows that the amount of global data generated and consumed globally is expected to reach 180 zettabytes by 2025. 

To address their growing data analytics needs, organizations are turning to cloud-based solutions. A cloud migration opens up a whole new world of opportunities for businesses, enabling them to connect disparate data sources and capture rich insights that drive informed decision-making.

A Cloud Migration Doesn’t Guarantee Enterprise Visibility

While a cloud migration offers several benefits such as centralized administration and improved performance, it doesn't guarantee that existing processes and tools will seamlessly integrate to deliver high-quality data. Achieving enterprise intelligence in the cloud goes beyond your technical capabilities; it’s about understanding how your people and processes work and aligning your tools to support them.

In this article, we give you the tl;dr (i.e. CliffNotes …or SparkNotes for our friends in Canada!) on how you can optimize your cloud environment to collect, analyze, and utilize data to make business decisions with confidence. 

Align Your People and Processes First, Then Your Tools Will Follow

A cloud migration or merge is a great opportunity to optimize your business processes and tools for improved decision-making. Whether it be because of exponential growth through acquisitions or consolidating instances to reduce costs, let’s take a look at four high-impact areas that organizations want to improve when transitioning to the cloud.

Software Development Lifecycle (SDLC)

Organizations are realizing that optimizing their software development process goes beyond having technical conversations; it also involves people, processes, accountability, and backing from leadership. When it comes to executing on what you plan to deliver, you need lean and consistent workflows. To achieve this, you must establish realistic data entry requirements that align with what your organization needs and that your teams understand. When your people understand the “why” behind the data they are entering, this results in more active participation and accountability–and in turn, better data. 

For example, we had an enterprise client whose teams had completely different understandings of hierarchies with issue types and features in Jira. Essentially, teams were blindly entering data without understanding its purpose, and the reports they generated weren’t telling the full story of how work execution connects to business strategy

The tl;dr on SDLC: Your tools can’t magically solve all your data management problems. Before you configure your SDLC, you must dig into company culture and your teams’ internal dynamics to make sure they understand the “why” behind the data they are entering. 

Capacity Planning Process and Resource Management

The capacity planning process is a controversial topic because there is a wide range of perspectives on how you should allocate resources. How do you capacity plan for what’s coming down the pipeline? How do you move your technical and people resources to get your strategic priorities done?

One big part of streamlining team capacity planning is creating consistent, intuitive configurations for measuring the level of effort for an individual work item. The more intuitive your data entry requirements, the more likely your people will understand the purpose of their work, and therefore, the more likely they will input good data. To do this, you must dig into how teams do the estimation and learn how leadership takes in that estimation.

The tl;dr on Capacity and Resource Management: Tools and their configurations play an important role in the capacity planning process, but they have to support how your teams calculate estimations and how stakeholders consume those estimations for them to work properly.

Strategic Planning

To put it frankly, getting to a place where you can plan what’s on the horizon for your business–whether that’s next month, next year, or even 10 years from now–is a long, arduous process. Sure, there are must-have cloud apps like BigPicture, Foxly, and Tempo Structure to assist you through the project planning process. However, identifying the people and workflows associated with prioritization at the team, project/program, and portfolio levels is where the real challenge lies with strategic planning.

We had a client looking to implement Lean Portfolio Management practices with Jira Align. While Jira Align is a great tool for this, it wasn’t the right tool for what the organization needed. Upon analyzing their instance, we discovered that different prioritizations were happening in silos within the organization. 

Before we could recommend the right portfolio management tool, we first had to understand what level of analytics the leadership team needed to see. From there, we identified all levels of prioritization and ensured that what teams were working on aligned with the customer’s strategic initiatives. 

The tl;dr on Strategic Planning: Once again, your tools aren’t going to save you when it comes to the project planning process. You must figure out prioritization at every level of the organization so that you can provide visibility into how all elements of your portfolio–big and small–roll up into your strategic goals and initiatives. 

Data and Business Analytics

How do you get the most out of the rich data that resides in your tech stack? And how do you do so in a way that allows you to make smart decisions for years to come?

A common scenario we see with our clients is they gather a lot of data and there’s no clarity around what they want to do with that data. To address this problem, you must understand what your leadership team is looking for and how they want to consume their analytics. 

Answering these questions will help you define a core set of meaningful data points that drive strategic decision-making across the enterprise. This will determine your data entry requirements so you can create intuitive and consistent field configurations that your teams understand and support accurate data.

Once you have your core data points and establish realistic data entry requirements, you can create powerful dashboards and reports curated to what your leadership team needs to see about how work at all levels of the organization (team, project/program, portfolio) tracks against strategic goals. With visibility into the right data, stakeholders can quickly make smart, confident decisions. 

The tl;dr on Data and Business Analytics: If your data isn’t meaningful and doesn’t speak to your company culture or what your leadership needs to see, then your tools will generate useless reports. To harmonize your data and use it to create valuable insights, you have to understand your people and their processes first, and then the tools and configurations will follow. 

The tl;dr on This Article

A cloud migration doesn’t automatically give you the ability to convert data into user experiences. If you want to make smarter and faster decisions, you need to have strategic conversations about aligning your technology with your people and processes. After all, your decisions are only as good as the quality of data used to inform them. 

Praecipio is all about building connected enterprises. By aligning your people, processes, and technology, we can help you achieve end-to-end visibility and create the real-time dashboards you need to make better business decisions. Reach out to our team to learn how we turn your data chaos into confident decisions that drive your business forward. 

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Achieve Enterprise Visibility in The Cloud

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