So you have a great idea for a new software application or system enhancement. Congratulations! However, before racing ahead to start development, it‘s wise to take an important step back and perform an objective feasibility assessment.
What Exactly is a Software Feasibility Study and Why Does it Matter?
A feasibility study analyzes whether a proposed software project is viable and likely to produce valuable outcomes efficiently. Teams use findings from structured feasibility analyses to determine if concepts make strategic sense to pursue further or if redirection is required before wasting effort and money developing the wrong solutions.
In other words, feasibility studies help ensure you build the right software systems – ones that solve real-world problems for users and deliver concrete business benefits. They provide validation to proceed confidently or prompt critical pivots when ideas that seemed fantastic on the surface prove problematic upon deeper examination across a variety of dimensions.
| Feasibility Study Goals | Importance |
|---|---|
| Identify flaws, risks, constraints early | Avoid wasted time and effort |
| Evaluate technical, operational, economic, legal, schedule viability | Determine well-rounded likelihood of success, not just isolated factors |
| Surface all assumptions and dependencies | Support fully-informed decisions on moving forward |
| Quantify costs versus benefits | Justify prudent investments |
| Document findings clearly | Enable data-driven choices to proceed, refine, or redirect |
Table summarizing goals and reasons feasibility studies are vital for software projects
Industry data underlines this value:
- 63% of software features are seldom or never used per recent surveys
- 68% of IT leaders say over half their development resources are spent on low-value work
- Companies that leverage pilot studies and gathering early feedback see 2x higher project success rates
In companies or teams that don‘t perform diligent feasibility analysis, wasted effort, gold-plating, and software failures are common. The opportunity cost and write-offs grow quickly substantial. That‘s why we‘ll walk through feasibility studies in-depth so you can improve outcomes for your own software initiatives.
A Brief History of Software Feasibility Analysis
Let‘s start with some historical context…
The origins of using feasibility principles during software design trace back over 60 years to the 1950s emergence of systems analysis approaches. As computing technology grew increasingly complex – involving mainframes costing millions – businesses needed ways to determine if proposals seemed strategically wise before allocating significant capital.
By the 1960s and 70s, assessing feasibility formally became a standard first phase of most systemic software development life cycles. Methodologies like the dominant classic waterfall model specifically mandated feasibility analysis before any actual coding or implementation work commenced. This preventative rigor saved many organizations from building intricate systems features that would never fulfill practical user needs or align with business goals months down the line.
Influential feasibility principles grew even more vital in the 1980s and 90s during rapid enterprise computing expansion. As networked client-server architectures as well as packaged software suites rose to prominence, companies had growing portfolios of interconnected systems. Evaluating the feasibility of any enhancement needed to consider bigger picture ecosystem impacts and dependencies – not software constructs in isolation.
Over the past two decades, feasibility analysis has remained essential in our current age of digital transformation and unprecedented application complexity. As Agile development grew popular, its emphasis on fail fast, continuous delivery, and embracing change requires vetting that only viable concepts survive initial scrutiny to avoid major rework. In modern DevOps practices and cloud-native architectures, successful outcomes also mean continuously re-assessing feasibility as requirements evolve across interdependent tools.
The common thread over 60+ years of software advancement has been projects set up for success when leaders first did their feasibility homework. With this historical foundation covered, let‘s dive deeper into common feasibility assessment types conducted.
Types of Feasibility Analysis Performed
There are five primary kinds of feasibility assessments leveraged to evaluate software designs from multiple angles:
Technical Feasibility
Technical feasibility evaluation determines whether the current hardware, software, and technology infrastructure can reasonably support the proposed application or enhancement. Relevant factors examined include:
- Servers, network capacity – sufficient compute resources?
- Existing software platforms, databases – compatible versions?
- End-user device readiness – supports needed functionality?
- Development team skills, capacity – can they build securely?
Pinpointing technical constraints, risks, or upgrade requirements early gives more options to formulate the optimal delivery strategy. Being forced to retrofit foundational components after launching adds substantial complexity. Let your technical feasibility findings guide strategic platform decisions and timeline planning rather than playing catch up post-release.
Example: assessing capability gaps for a future system that must leverage AI and data science
| Dimension | Current State | Gaps for Future |
|---|---|---|
| Server Hardware | Standard on-premises servers 6 years old | Lack GPU/TPU processing power for ML |
| Data Pipeline Tools | Basic ETL and DBs | No data science workflow automation |
| Team Skills | SQL, software development | Minimal statistical, mathematical expertise |
| Cloud Strategy | On-premises only | Requires scalable cloud platform |
Technical feasibility analysis revealing where infrastructure and skills lag for a proposed AI system
Operational Feasibility
While a software concept might seem technically sound, that means little if it doesn‘t actually help your business or customers handle tasks more efficiently. Evaluating operational feasibility keeps developers grounded in solving real-world workflow issues by proactively gathering user input.
Interview end-users, process owners in different business units, and other stakeholders. Capture their current pain points and desires for improvement. If a proposed system aligns poorly with actual needs or interfaces poorly within ecosystems, pushback awaits no matter how elegantly coded the software. Prevent this dynamic by rigorously assessing operational feasibility factors:
- User workflows – facilitates or complicate these?
- Process change impacts – minimal or major?
- Learning curves – gradual onboarding or steep?
- Cultural adoption risks – resistance factors?
Addressing these considerations upfront, while adjustments cost less, results in far smoother change management later on. You don‘t want to be explaining to managers why a delivered application causes more headaches than curing them!
Example: highlighting red-flags uncovered when evaluating user impact
| Feature | Finding | Risk Rating |
|---|---|---|
| Single sign-on access | Confuses basic computer users | High |
| Visually complex dashboards | Steep learning curve for field teams | Medium |
| Restricts tool flexibility | Engineer resistance predicted | High |
Key findings from an operational feasibility study showing flagged user experience gaps
Economic Feasibility
At the end of the day, software investments must make prudent financial sense too. Economic feasibility compared projected costs across not just initial development but ongoing future licensing, maintenance, administrations and opportunity costs against potential quantified benefits:
- Development costs – contractor fees? Cloud services?
- Implementation costs – training, testing, deployment
- Ongoing costs – admin, troubleshooting, licenses
- Business benefits – efficiency gains, new revenue?
Run the numbers to validate a positive projected return. Leaders can then allocate budgets and expect measurable ROIs based on rational projections vs intuition.
Example: summary view of key cost and benefits projections
| Costs | Total Estimate | Benefits | Total Estimate |
|---|---|---|---|
| Development | $250,000 | Increased sales conversion rates | +$500,000/year |
| Cloud services | $12,000/year | Decreased customer service case volume | +$75,000/year efficiencies |
| Maintenance team | $60,000/year | Faster complaint resolution | +$100,000 value |
| Training | $35,000 |
High-level economic feasibility analysis results
Legal and Regulatory Feasibility
With data privacy regulations multiplying, no software rollout comes without compliance considerations. Ignoring legal feasibility early on jeopardizes initiatives down the road. Have your design specifications and plans reviewed to avoid issues like:
- Industry data handling policies – HIPAA, PCI, etc.
- International laws – GDPR, data residency
- Encryption standards
- Licensing terms
- Intellectual property protections
Adjusting trajectories is vastly simpler than reacting to infringements or audit penalties later that put projects in legal limbo. Don‘t skimp on legal feasibility homework especially given shifting policy landscapes.
Example: summary of key legal feasibility risks identified
| Area | Findings | Severity |
|---|---|---|
| Data retention policies | Proposed 5 year retention beyond EU GDPR standards | High |
| Encryption protocols | Fail to specify FIPS 140-3 or later standards | Medium |
| Open source usage | No guidelines for tracking licenses, attributions | Low |
Excerpt from legal feasibility analysis results
Schedule Feasibility
The final feasibility lens focuses on validating if proposed delivery timelines and milestones seem achievable for a project or if reliance on overly aggressive assumptions risks major delays. Be honest about activity durations, accounting for testing, integration, likely rework etc. Build rough plans with key phases and checkpoints.
Common areas to assess schedule feasibility for include:
- Overall timelines – roadmap phases
- Resourcing models- are staffing levels realistic?
- Milestones – dependencies identified?
- Delivery commitments – buffer time included?
Err on the side of conservatism in your projections and buffers. Surprising stakeholders with an early delivery always goes over better than perpetually missing deadlines. Plan for probable interruptions spotting schedule gaps improves the outcomes.
Example high-level schedule with feasibility risks flagged
Simplified roadmap view calling out schedule feasibility risks
Evaluating all five areas in tandem – technical, operational, economical, legal, scheduling – provides comprehensive feasibility grounding. You get an empirical basis for judging the overall likelihood of delivery success. Armed with these insights, let‘s shift gears to constructing the artifacts themselves.
Constructing Your Own Feasibility Study
We‘ve covered why feasibility matters and different lenses commonly analyzed. Now, let‘s walk through how to actually conduct an assessment by constructing a feasibility study document. Follow these steps:
1. Define the Problem
Don‘t jumped ahead to your exciting solution without framing the underlying problem first. Outline the business or technical shortcoming the proposed software aims to improve. Reference supporting data like falling conversion rates or rising service ticket volumes indicating there are issues. List affected workflows and user personas to keep the needs tangible.
2. Analyze As-Is State
With the problem defined, objectively detail the current software environment and processes related to this problem space. Resist touting consolidation capabilities yet. Simply document facts around where systems, data, and policies presently stand. Also capture any pain points users share about their daily experience. This analysis contextualizes gaps.
3. Envision the Future State
Next, summarize at a high-level what you envision the proposed software changes or new solutions doing differently regarding the focus area analyzed. List desired future capabilities and other components that would address identified deficiencies and needs.
4. Conduct Feasibility Assessments
This section covers the detailed feasibility analysis to validate if the theoretical solution seems viable. Perform technical, operational, economic, regulatory, and scheduling assessments as previously covered. Document all findings, risks, dependencies, cost projections etc. that emerge.
5. Complete Cost/Benefit Analysis
With all feasibility research complete, summarize financial costs for development, licensing, maintenance, training etc. and compare against quantified benefits like enhanced productivity, lower IT support burden, and increased revenue.
6. Make Recommendations
To conclude the study, offer recommendations on whether moving forward with the defined software plans seems justified or if certain changes are advised first to address flagged constraints. Provide any other guidance useful for stakeholders and decision-makers relying on these findings.
Now that you understand the anatomy of a robust feasibility study, let‘s examine some real-world examples that brought lessons learned to light.
Real-World Feasibility Studies: Case Examples
Consider these real project examples that demonstrate the business value feasibility assessments delivered:
Proposed HR System Consolidation
- The technical feasibility study revealed that combining six legacy HR platforms into a single system carried high change management risks. Instead of forging ahead, findings were used to shift priority to modernizing one HR application first then assessing expandability. This prevented overextension technically and operationally.
Mobile Field Inspection Application
- Despite enthusiastic initial reactions from operations leadership during interviews, detailed operational feasibility analysis surfaced that field inspectors had concerns about required data entry on smaller form factors. Findings prompted mandating tablet-based devices rather than phones to ensure usability.
AI Chatbot for Customer Service
- While conversation AI technology has matured significantly, an economic feasibility study determined developing custom chatbot capabilities was still prohibitively expensive for customer volume. Leadership instead prioritized enhancing self-service knowledge base to better leverage existing platforms first.
In all cases, critical development flaws were caught early enough that projects could be re-scoped, resourced, or re-prioritized as needed based on objective feasibility constraints uncovered pre-development. The findings quantitatively supported strategy pivots before resources were committed.
In Closing: Key Feasibility Study Takeaways
By now, it should be clear that comprehensive feasibility analysis brings immense value during software planning stages. At its heart, structured feasibility assessment determine if a proposed system or enhancement is truly viable across the core dimensions of technology, operations, cost efficiency, compliance, and achievable timelines.
Wise IT leaders and architects leverage feasibility study findings to guide data-driven decisions on whether moving forward with solution designs warrant greenlighting or if prudence calls for redirection. I hope walking through real examples demonstrated that this isn‘t just theoretical but highly practical.
To recap, remember these key lessons:
- Conduct assessments before writing any complex code to prevent wasted effort
- Evaluate technical, operational, economic, legal, schedule viability holistically
- Clearly define as-is problems then envision future capabilities
- Compare quantified costs and benefits to validate ROI
- Document all risks, constraints, assumptions surfaced
- Leverage findings to justify proceed forward or make strategic pivots
With this comprehensive understanding of feasibility analysis fundamentals now in hand, you‘re equipped to evaluate proposed software designs through an objective lens. Just remember that not every idea pans out exactly as initially envisioned – but diligent feasibility inspection sets your team up to navigate obstacles and maximize the likelihood of eventual success when projects launch.
Hopefully this guide has shown that feasibility homework isn‘t busywork but pays real dividends for tech leaders overseeing critical software modernization initiatives. Here‘s to fewer surprises and more insights along your journey leveraging feasibility studies!
