Burning deadlines, climbing costs, unmet expectations of partners, and scope creep turn your project into a nightmare. No worries, we’ve got a remedy for that: the discovery phase. With this homework adequately done, you will enjoy it the smooth way. So, let us dive right into it.
Before we delve into the discovery phase of software development, let’s start with the broader perspective to understand the fundamental idea behind it better. Usually, a project’s lifecycle includes the following stages: initiation, planning, execution, control, and closure. Of course, the better base for your project you provide within the initiation stage, the more smooth way you and your team can follow later.
However, reality dictates: that you can be under pressure to provide the deliverables, upfront research is a luxury you can not afford, or you might think that you know enough for launching. And then the particular adrenaline-generating stage begins, not mentioned in the project manager’s tutorials: scope creep, burning deadlines, climbing costs, and unmet expectations of your teammates, clients, and even yours.
Thus, it is worth investing time and effort in the discovery phase of your project, both for fixed costs and agile ones. By the way, check out our blog if you are new to Agile methodology.
In essence, the discovery phase (or business discovery stage or scoping phase) of a project is all about the research and the project’s scope defining. In other words, it is a preparatory stage of your project, when you collect and analyze information, and research your audience and intended market. Technically, the business discovery page leads to the system requirements specification (SRS), including details needed for development.
Given the project’s scope, the discovery phase can take from one week to two months. Usually, the scoping phase involves the project manager, business analyst, and account manager. Depending on the project, UI/UX designers, developers, and team leads can join the discovery phase to help with wireframe prototypes, SRS, or scope assessment. A couple of meetings are required initially, and then the later process does not need constant input from your side.
It depends on the idea of your project, but we try to give you some gist so that you can outline your scope of work. For example, the business scoping phase might imply the following activities in most cases:
We advise running user research to define their pain points and goals and go deeper than operating with demographics. The next component of this step is to present the results to all the stakeholders, and customer journey mapping is among the most appropriate tools for it.
Well, running a project without clear goals is possible, but it’s like using a banana instead of a gun at the shooting gallery. Speaking more formally, projects with no goals established are prone to scope creep, missed deadlines, and overspent budgets.
Of course, one of the most popular indicators of success is a return on investment (ROI), but what if some stakeholders focus on the engagement of digital products, not on leads? It is better to decide it at the outset. We recommend benchmarking the success of your project against the existing services (e.g., previous version) or establishing your key performance indicators with your team.
At this stage, it is time to define what exact value your project provides to the end-user and what features of your product or service are delivering those benefits. Otherwise, it is useless to communicate your product to the end-user.
Finally, any digital product can not exist in a vacuum, so you should consider things like internal politics, compliance issues, or technical limitations. Simultaneously, it is worth spending time analyzing the competitive landscape and reviewing existing services or products.
Aside from feasible outputs like UX prototypes, SRS, MVP, and estimates, you can enjoy the following benefits after the successful scoping phase:
Risks mitigating
When all your teammates have a clear vision of the project’s goals and requirements, it is natural that budget overspending and missed deadlines are less likely to happen.
Staying on the same page
The discovery phase is the best time to clarify all the questions and understand the peculiarities of your project with vendors. Thus, you can be sure that all stakeholders get the desired result, and it is much better to synchronize all the questions during the scoping phase than to make a pricey Change Request later.
Project roadmap creating
When you successfully finish the project’s discovery phase, you can have a detailed plan with timelines from ideation to launch. It is also possible to flexibly align it to any possible changes.
Testing your IT vendor
The discovery phase is high time to reveal whether you and your IT vendor speak the same language so that you can rely on them entirely during the project implementation.
The discovery phase of AI-driven projects differs from the usual ones. For instance, stages like data cleaning and data infrastructure setup are much more linear than typical software development processes. Consequently, you might need a different project management methodology and focus on more processes and assets to manage.
We hope that our template for your discovery phase within the AI project will come in handy. Enjoy!
Outline prerequisites: define the end-user of the machine learning (ML) product and available data pools. As a rule of thumb, remember that the better data you have, the better outcomes your ML model can generate. However, usually, businesses do not have access to clean and structured data, and data analysts, data engineers, and data scientists can help with it. Usually, they iteratively clean data, gradually increasing the volumes of datasets, leading this process in parallel with other ones.
Define data scope and infrastructure: you should consider the data infrastructure for your AI project. For example, find out the answers to the following questions at the outset. Where should you deploy your MLml models?” Who will manage the data to exclude the data decay? Is the data locality problem applicable to your case?
Build your dream team: data analysts, data engineers, data scientists, or infrastructure engineers? Besides being specialists in the same domain, each of them might have their particular skill set to meet your expectations. Also, define the single point of contact (SPOC) on the client’s side at the outset.
Set goals and define success: how will you benchmark your AI product to measure its effectiveness? You might have some brainstorming sessions with your team to set your own KPIs for the project. We recommend prioritizing your MVPs, as a working prototype of a product is better than presenting an unfinished one.
To make the best of the discovery phase, consider the following:
Let the discovery phase be proportional to your project
People often ignore the scoping stage as they think of this as a time-consuming practice. However, the trick is to make it proportional — a single short meeting with the crucial stakeholders for a quick project. Plan a couple of sessions for long-term projects. The output you get is precious in any case.
Make sure everyone is included in the discovery phase
By default, you will benefit when all of your team that can impact the project is involved in the scoping phase. Thus, it helps to establish communication at the outset and escape the misunderstandings further.
Spare some time for user interview
It is always better than relying on personas or rough demographic data only. Make sure that your colleagues are involved. At least they can watch the interview recordings.
Communicate with all stakeholders
It helps minimize the risks when some potential influencers can express their dissatisfaction in the middle of the project. Again, the scoping phase — is the time when all the expectations can be met.
Let your discovery phase be a small project with defined deliverables
It is beneficial for outside agencies, as you can try the working relationships with your new client and move to the first small goals set.
The discovery phase is the practice of collecting and analyzing all the relevant information regarding your project, audience, and intended market, setting clear goals, and defining the indicators of success. In other words, it is the preparation stage within the initiation stage of your project’s lifecycle. When successfully running, you can enjoy outputs like UX prototypes, SRS, MVP, and time and cost estimates that could be invaluable at the beginning of your project.
