Data R&D Journey #2: The Path to Deeper Understanding
See if this scenario sounds familiar: your business needs to make better decisions, faster. On one hand, you've got a data problem. Your data comes from many different sources - it's hard to know which data represents the "truth". Your people are passing around multiple versions of the same spreadsheet that always seems to be out of date.
On the other hand, you have an analysis problem. You can do basic counts and aggregations, but success or failure will depend on much more than simple analyses. To see deeper into your data, you’re going to need to get out of Excel and start leveraging a BI tool. Your company needs insights on demand, and certain problems may require creating a simulation or predictive model. At the end of the day, you need your speed of insight extraction to keep up with the pace at which business-critical decisions must be made.
Organizations on the insights journey are essentially looking to increase the frequency and quality of their analyses to fuel deeper insights and better decision-making. This might involve:
Structuring and organizing data;
Creating or improving databases;
Setting up Business Intelligence (BI) tools;
Developing dashboards, visualizations, and models ;
Integrating new data sources;
Developing new processes to give the right people access to data on demand.
Today, we’re going to dive into the insights journey as part of our series on the four different types of data-intensive R&D journeys. We’ll cover how to get started, the risks and rewards, and the stakeholders you’ll need to align to ensure the project’s success. Let’s get started.
Where are we going on this journey?
There are many types of insight journeys. Maybe you need internal search engines to increase the efficacy of your support team. Maybe you need better business intelligence to support a new line of business. What about some interactive dashboards so your stakeholders can pull their own reports ad hoc instead of relying on analysts to do it for them? Or perhaps you want to build predictive models to assess customer churn risk.
The successful end state of this journey means your business is getting more value out of its data, and your team is empowered to make faster, better decisions for your business.
Any journey has possible end points that are good, bad, or ugly. Some examples:
Good → New, faster insights lead to better decision making.
Bad → Data quality issues lead to incorrect insights and poor decision-making.
Ugly → Despite having new, data-driven insights available, many employees and managers continue to rely on gut feelings or outdated processes, negating the potential benefits of the new system. Or conversely, the new system works so well that the organization becomes overly dependent on it, potentially losing critical human judgment and intuition in decision-making processes.
The risks of this type of journey often include:
The organization has a vast amount of insights, but finds it lacks the capacity or skills to effectively act on the information.
The new insights reveal that the org has been focused on the wrong KPIs due to bad data going into the system.
Acting on the new insights leads to unexpected negative outcomes in other areas of the business, revealing complex interdependencies that weren't initially apparent.
But if you embark on this journey with clear goals, well-aligned stakeholders, and reasonable expectations for your organization’s pace of change, the many compelling rewards at journey’s end can include:
A culture rooted in data-driven decision making becomes the norm across the organization;
Enhanced collaboration between departments due to shared data access;
Significant time savings in report generation and data analysis;
Increased ability to identify trends and opportunities in real-time.
Who are my traveling companions on this journey?
On any data R&D journey, there are decision makers and gatekeepers.
Decision Makers are usually:
Executives and senior management, in particular:
The CDO or CIO (or whoever is responsible for your organization’s data. They’re usually your champion - the person instigating this journey.)
Gatekeepers often include:
IT/Compliance - “The old system was working safely! Change is too big a risk!”
Finance - “Why are we spending all this money? Prove the ROI to us.”
Who benefits from this journey?
Just about everyone in your organization can benefit from better insights. People at all levels spend less time waiting around for updated analyses. Everyone always knows they’re looking at the most recent data, so the quality of decision making goes up while the frustration about uncertainty goes down. There are fewer tradeoffs between data gathering and decision making.
Your only negative beneficiaries might be those employees who find career value in being organizational data gatekeepers. What happens when their managers have access to self-service data tools?
How to get started
While every company's destination is unique, we have seen patterns in how these journeys start. The three main stages of the Insights journey are typically:
1) Data Warehouse Design & Implementation
To start, we’ll design and implement a scalable and secure data warehouse architecture that centralizes and organizes your data, enabling efficient storage and rapid retrieval. We’ll set up data models, ETL processes, and tools for security and compliance. The most important part is that we’ll work hand in hand with your team the entire way, so that they understand what’s happening under the hood, and can troubleshoot and improve things on the fly going forward.
2) Data Systems Integration
Next, we'll get your data systems talking to each other. No more emailing versioned spreadsheets and triple-checking whether a data point is from today or from last month. You'll have a central repository for business data, providing a reliable foundation for decision-making processes and future data-driven initiatives. We'll integrate your key data sources with the systems that need that data as input. Live feeds of structured, organized data give your systems, and more importantly your people, a comprehensive and up-to-date view of the business.
3) BI Tool Configuration & Dashboard Development
Finally, the fun part. We'll set up a Business Intelligence (BI) tool that plays well with your systems. No more digging through spreadsheets or waiting for reports. We'll build user-friendly, web-based dashboards that let your people interact with data in real-time. You'll spot trends, catch issues early, and track your progress towards goals. Best of all, you'll be fostering a data-driven culture that'll speed up decision-making across your whole organization. Congrats! Now you're turning your data into your secret weapon.
These are just the first steps. Your company's KPIs may change over time and your company may want to socialize the ability to create dashboards. Or your team may need to tackle some more advanced questions that require data science, AI/ML, or predictive techniques.
As we’ve seen, the journey to deeper analytical insights is a transformative process that can revolutionize how your organization makes decisions. While it requires time, resources, and careful planning, the potential rewards are substantial. From faster decision-making to a more data-driven culture, this journey can give your business a competitive edge in today's fast-paced market.
But remember, the path to insights is not just about implementing new tools or processes—it's about fostering a mindset that values data and embraces continuous learning and improvement. As you embark on this journey, keep your goals and expectations aligned to your business objectives. The journey may have its challenges, but with the right approach and support, you'll be well-equipped to turn your data into your organization’s most powerful asset.
Our next post will cover the 3rd data-intensive R&D journey: The Search for Stability. But if you’re ready to jump ahead and get started on your own journey, why wait? Let’s chat now.