Business and technology leaders are expected to deliver data and analytics initiatives that move the business forward and provide measurable business outcomes and value. But D&A initiatives are notoriously challenging, and the vast majority fail to deliver the value promised.
Gartner articulates the challenges perfectly in Top Priorities for IT: Leadership Vision for 2021:
“… [C]hronic issues have become more acute. Siloed data, lack of trust, misalignment to outcomes, a focus on data for its own sake and an assumption that a technology acquisition will be sufficient can be colossal challenges to overcome because there is no quick fix.”
Forward-thinking, future-oriented data leaders are looking for a new way to deliver business value. But before you can move forward, it’s important that you identify which stage of data delivery your organization currently falls into.
In this piece, we’ll examine the three stages of data delivery that every organization goes through, and guide you to the most mature stage of data delivery, based on product management principles.
Stage 1: Transactional or request-based data and analytics delivery
Accepting a request and delivering a data set
The first stage of data delivery is transactional or request-based.
Most organizations start here. Typically, at this stage, one individual or sometimes a small team of IT professionals is responsible for delivering reports on a recurring or ad hoc basis. Business leaders make a verbal or written request, and IT delivers the report.
In some organizations, IT even has a centralized ticketing system in place where stakeholders can request analytics in a more formalized process.
Data professionals know this stage well. And you know just how frustrating it can be.
Because, under the hood, it’s never as simple as submitting a request for say, a 2021 Black Friday sales forecast based on the last two years.
The challenges inherent in request-based data delivery are often hidden from executives who only see the end result. They don’t have visibility into the multiple email chains necessary just to determine where the correct data resides; the data pull from three different systems, followed by data quality checks; and the one-time manual updates and data set linking that goes on in the background.
This transactional reporting is inefficient, not scalable, and worst of all wastes your data talent on repetitive, low-value work.
Stage 2: Project-based data and analytics delivery
Understanding requests and delivering point solutions using a project management lifecycle
The next stage of data delivery is project-based. This data delivery model is certainly more organized and efficient than the first. In larger enterprises that have moved beyond a request-based approach, this is how most traditional data and analytics efforts are delivered.
During this stage, organizations will typically allot a portion of IT’s budget towards a data modernization project that aims to take some of the pressure off of IT by centralizing data and creating self-serve reports that can be accessed by business leaders across the organization. Leveraging classic project management techniques, the project owner compiles the requirements (often without consulting the lines of business) and scopes out the project plan while IT sources the tech. They may even bring in a consultancy to assist for the duration of the project.
The project team stands up a data warehouse, creates a few standard reports for finance and marketing… and that’s it. Project over.
While a project-based data delivery model may be more efficient than a request-based model, in truth it’s a short-term, band-aid solution that doesn’t solve the long-term challenges facing businesses.
As business needs change, old reports become obsolete. New data and analytics needs arise, so IT and data teams are once again forced to build ad hoc reports.
Additionally, there is the creeping risk of shadow IT as departments purchase non-vetted software that provides them with some of the insights they are looking for.
Luckily, there is a better way.
This leads us to our final stage of data delivery maturity…
Stage 3: Product-based data and analytics delivery
Understanding business user outcomes, delivering using a project management lifecycle, and focused on end-user adoption
It’s time for a change.
A new approach has emerged. Companies are starting to approach the analytical needs of the business using a product management framework.
Instead of gathering rigid requirements and focusing on milestone deliverables, product management empathizes with the end-user and strives to define their challenges. It uses a technique called design thinking—used by SaaS and B2C companies to build successful products for years now—to understand the end-users needs’, define the challenge they’re facing, and iteratively build a solution that solves their challenge.
The end-users in our scenario are the business leaders who use data and analytics to make strategic decisions. With a product management approach, these end-users are involved in product development throughout the entire process. This ensures that solutions are tailored to their changing needs, deliver measurable business value, and solve the problem of low user adoption.
Product management also differs from project management in that it delivers value fast. Instead of waiting until the end of a 6-12 month period to show value, product management is designed to deliver business value within weeks with an MVP.
But it doesn’t end at MVP. The product management approach to data delivery is an iterative, long-term engagement that produces value over time as it stays in lockstep with the needs of the business user.
So, what’s happening under the hood now when an executive opens their dashboard and reviews a report?
It’s simple, clean, and automated. No more email chains, manual data quality checks, and meetings to determine where the right data lives.
Instead, automated systems refresh data nightly and perform linking and data quality checks. Reports are automatically updated with new data before the start of the business day.
With a product management approach to data delivery, business leaders can be successful in their role because they have access to the data-driven insights they need to make better business decisions.
IT can focus on high-value, skills-based work instead of generating time-consuming one-off reports.
And CDOs and other data leaders have the data tools to take the business to the next level, in an organization where data and analytics are viewed as a key component of business success.
Use a product management approach to deliver business value
Are you prepared to challenge the status quo and transform your data into meaningful insights?
With a product management approach, you can bring your business to the next level and start delivering data that is aligned with business goals and outcomes.
Are you prepared to shift the mindset at your organization?
If you’re ready to move into the product management data delivery phase, we can help.
At Gensquared, we start by empathizing with your business, which means understanding your business goals and speaking to your end-users—whether that’s marketing, finance, sales, HR, or operations—to understand what data and analytics they require to meet their business needs. Only then can we work with you to transform your data into actionable insights.