If your business runs on software (and whose doesn’t now?), the real question isn’t “What tools do we use?” but “Are we actually managing them properly?”
This article walks through the major dimensions you need to think about when supporting, managing, optimizing, scaling, integrating, and getting real value from your software stack – from SaaS and COTS to legacy, niche, custom, and web/PWA apps. I’ll weave in stats and facts along the way so you can also use this as internal “ammo” with leadership.
1. The Modern Reality: More Apps, More Risk, More Opportunity
Even small and mid-sized businesses are now sitting on surprisingly large software portfolios:
- Companies use an average of 112 SaaS apps, with SMBs (under 200 employees) still averaging about 42 apps.
- Some reports show organizations using around 220 SaaS apps on average as of 2024.
But:
- Organizations only use about 47–60% of their SaaS licenses, with the rest wasted – translating into $18–21M/year in unused spend for larger orgs.
Even if your SMB numbers are smaller, the pattern is the same: too many tools, not enough strategy, and a lot of hidden risk and waste.
The rest of this article breaks down the key lenses you should use to evaluate and manage your software ecosystem.
2. Business Alignment & Value: Is the Software Actually Serving the Business?
Most organizations start with, “What can this tool do?” instead of, “What is this tool doing for us right now?”
Key considerations:
- Clear purpose & ownership
- What business outcome is the system supposed to drive? (Revenue, efficiency, risk reduction, CX, etc.)
- Who actually “owns” it internally? (Not just IT – but a business owner who cares about outcomes.)
- ROI & TCO (Total Cost of Ownership)
- Licensing + implementation + support + integrations + internal time + training.
- Are you using 20% of the features but paying for 100%?
- Utilization & adoption
- Are licenses actually used?
- Are key features being leveraged or are people working around the system?
With so many organizations wasting 40–53% of SaaS licenses, a basic utilization review is often low-hanging fruit for reclaiming budget and focusing on the right tools.
3. Security & Privacy: Protecting the Stack and the Data
Security isn’t just “IT’s problem” anymore. It is a core business risk area:
- The average global cost of a data breach is around USD $4.4–4.9M, depending on the year and sector.
- AI and “shadow AI” incidents are increasing breach costs even further.
For SMBs, you may not see multi-million numbers, but the proportional impact can be just as devastating.
Security considerations across software:
- Identity & access management
- Role-based access, least privilege, SSO, MFA, offboarding processes.
- Vendor security posture
- SOC 2, ISO 27001, penetration tests, secure SDLC, incident history.
- Shadow IT / Shadow SaaS / Shadow AI
- One recent report notes SMBs now averaging 275 SaaS apps, with only a quarter IT-approved, and tools emerging specifically to manage this risk.
- Data handling & privacy
- PII, financial, health, and customer data: where is it stored, who can access it, how is it encrypted?
Security is not just about preventing incidents – it’s about reducing blast radius when something goes wrong and ensuring your stack is governable.
4. Compliance & Regulatory Considerations
Depending on your industry and geography, your software stack needs to support:
- Data protection laws: GDPR, CCPA, PIPEDA, etc.
- Sector regulations: HIPAA, PCI DSS, SOX, ISO standards, industry-specific QA/traceability requirements.
- Audit trails & reporting: Who did what, when, and in which system.
- Retention & deletion policies: Data minimization, right to be forgotten, legal holds.
Many tools technically support compliance, but only if they are:
- Implemented correctly
- Integrated into policy
- Supported with training and documentation
Compliance is part configuration, part process, part culture.
5. Performance, Reliability & Uptime
Even if you are “just an SMB,” downtime and performance issues still hurt:
- The estimated cost of downtime often ranges between $100,000 and $300,000 per hour, with some studies showing over $1M/hour in certain cases – and this pattern holds even down into the SMB range when you factor in lost sales, productivity, and recovery costs.
Core considerations:
- Uptime and SLAs
- Vendor SLAs (99.9% vs 99.99%)
- Internal SLOs for critical systems
- Monitoring & alerting
- Are you proactively notified of performance degradation or just hearing about it from users?
- Capacity & scaling
- How does the system behave under peak load?
- Resilience & failover
- Backups, DR plans, RPO/RTO.
For custom, legacy, and niche tools, you often need explicit investment to bring performance and monitoring in line with modern expectations.
6. Integrations, Dependencies & the Silo Problem
Integration is where a lot of value is created – and where a lot of pain lives.
Reality check:
- One recent analysis found only 28% of enterprise applications are integrated, despite organizations using on average 897 apps, creating huge data silos and blocking AI and analytics initiatives.
- 81% of IT leaders say data silos are hindering digital transformation, and 62% say their systems are not configured to fully leverage AI.
For SMBs, the numbers are smaller but the pattern is the same: separate systems for CRM, ERP, WMS, ecommerce, support, marketing, field service, finance, etc.
Integration considerations:
- Critical data flows: What actually needs to move between systems (e.g., customers, orders, inventory, tickets)?
- Integration patterns: Point-to-point, hub-and-spoke, iPaaS (Zapier/Make/Workato), custom APIs, webhooks.
- Error handling & monitoring: What happens when an integration fails?
- Upgrade impact: When one system updates its API, what breaks?
- Vendor roadmaps: Are you building into something the vendor will deprecate?
When integrations are neglected, you get duplicated data, conflicting truth, and manual spreadsheet workarounds – the exact opposite of what software is supposed to deliver.
7. Data, Analytics, and “Dark Data”
You can have perfect systems and still fail if you do not use the data they generate.
Key stats:
- IBM and others estimate that 50–60% of organizational data is “dark”, collected but never analyzed or used.
- Knowledge workers spend around 20–25% of their time just searching for information, not acting on it.)
Data considerations:
- Single source of truth
- Does your organization agree where “truth” lives for customers, inventory, orders, projects?
- BI & visualization
- Are key metrics surfaced in dashboards or buried in exports?
- Data quality & governance
- Ownership, definitions, naming standards, validation rules.
- Storage & retention
- Are you hoarding data you never use, paying to store it, and increasing breach risk?
The gap between having data and using data is where a lot of competitive advantage can be found, especially for SMBs.
8. User Experience, Training & Adoption
A system that is “technically powerful” but painful to use will quietly fail.
Signs you have a UX/adoption problem:
- People track work in their own spreadsheets or side tools.
- Multiple “versions of the truth” are floating around.
- New hires take way too long to ramp up.
- “I didn’t know the system could do that” is a frequent phrase.
Research suggests employees can spend the equivalent of a full workday per week searching for documents and information.
Things to consider:
- Information architecture
- Labels, navigation, hierarchy, search.
- Training & internal champions
- Do you have structured onboarding, refresher training, and FAQs?
- Embedded help & knowledge bases
- In-app help, tooltips, SOPs, and “how-to” flows.
- Feedback loops
- Is there a way for users to suggest improvements or report friction?
This is exactly where structured training and knowledge systems and “champion” roles become critical.
9. Maintainability, Technical Debt & Refactoring
Even great systems accumulate technical debt over time:
- One survey found 92% of organizations are burdened by technical debt; 80% reported it delayed or canceled business-critical projects and 79% said it raised software costs.
- Another analysis estimated developers spend up to 42% of their time dealing with technical debt rather than building new features.
Debt isn’t just code; it exists in:
- Old workflows and workarounds
- Legacy integrations
- Poorly documented configurations
- “Temporary” fixes that became permanent
To manage it:
- Regular refactoring & cleanup cycles
- Deprecation strategy for outdated features and tools
- Architecture reviews
- Documentation as a first-class deliverable
Ignoring technical debt turns your stack into a fragile maze that becomes harder and more expensive to change every year.
10. Scalability & Future-Proofing
You don’t just need systems that work today. You need systems that can support:
- More users
- More transactions
- New locations, markets, channels
- New business models (subscriptions, ecommerce, services, etc.)
Consider:
- Capacity limits: API rate limits, storage caps, seat limits, table/record limits.
- Multi-entity support: Multi-company, multi-currency, multi-warehouse, multi-language.
- Extensibility: Plugins, APIs, webhooks, custom objects.
- Cloud region & latency: Where your traffic and customers actually are.
“Cheap and cheerful” tools that are fine at 10 users may be painful at 100 and unworkable at 500.
11. Accessibility, SEO, and LLM Optimization (Especially for Web Apps & Sites)
For websites, portals, and web apps, there are three often-underrated lenses:
Accessibility
- Adhering to WCAG and local accessibility regulations is both a legal and ethical requirement.
- Screen-reader support, proper semantic HTML, contrast, keyboard navigation, captions, etc., all affect who can use your app.
SEO
- For public-facing sites, you want search engines to understand and surface your content:
- Clean URLs, meta tags, structured data, site speed, mobile responsiveness, content quality.
LLM Optimization (AI/Chatbots/Search)
Increasingly, users discover and interact with content via LLMs and AI assistants:
- Having structured, clear, up-to-date content, documentation, FAQs, and schema helps both internal and external AI tools make sense of your business.
- Fragmented or siloed data (as many AI/readiness studies point out) is a major blocker to effective use of AI.
If you want AI to help you or your customers navigate your stack, you must design your systems for machine as well as human comprehension.
12. Cost Management, Licensing & SaaS Sprawl
SaaS sprawl and license waste are not just enterprise issues:
- Organizations on average use 112–220+ SaaS apps, with large portions of licenses remaining unused, wasting tens of millions annually at scale.
- Shadow IT and unapproved SaaS/AI use are rising fast; some research suggests up to 75% of employees may use unauthorized tech by 2027.
For SMBs, the challenges look like:
- Multiple overlapping tools doing similar things.
- “Free” or cheap tools that become embedded and then expensive at scale.
- Renewals on auto-pilot with no utilization review.
- No clear picture of total software spend.
Good practice:
- Central inventory of tools (including integrations and scripts).
- Regular license and utilization reviews.
- Standardized procurement and de-provisioning processes.
- TCO models that look beyond sticker price.
13. Governance, Ownership & Operating Models
Even a brilliant set of tools will fail without a governance model.
Questions to answer:
- Who is responsible for:
- Overall architecture and stack roadmap?
- Each major system (business owner + technical owner)?
- Approving new tools and integrations?
- Decommissioning old ones?
- How are decisions made:
- To adopt, integrate, customize, or retire software?
- How are standards enforced:
- Data definitions, naming, documentation, access, backups?
This is where models like internal champions, application management partners, or hybrid arrangements become key.
14. Internal Champions vs External Application Partners (Like Us)
There are three broad approaches:
1. Fully Internal Champion Model
You hire and grow internal champions who:
- Own systems day-to-day
- Manage configurations and integrations
- Drive training and adoption
Upside: Deep internal context.
Downside: Keyman risk, hiring and retention challenges, limited breadth across many tools.
2. External Application Management Partner
You appoint a partner (like Champion1) to act as your application champion:
- Single source for support, optimization, integration, documentation.
- Continuity even when your staff changes.
- Cross-tool experience from working across many stacks and industries.
Upside: Breadth, continuity, lower internal burden, structured governance.
Downside: Requires strong collaboration and clear boundaries with internal teams.
3. Hybrid Model
You maintain internal champions and leverage an external partner for:
- Higher-level integrations and development
- Architecture and roadmap
- Complex migrations and modernizations
- Training systems and knowledge frameworks
This often gives SMBs the best of both: internal ownership plus external horsepower.
15. Bringing It All Together: A Checklist View
When you think about your software and applications, consider:
- Business Alignment – What is this tool for, and is it delivering?
- Security & Privacy – How is data protected, and where is risk?
- Compliance & Auditability – Can we prove what we need to?
- Performance & Uptime – Is it fast, stable, and monitored?
- Integrations & Data Flow – Does data move where it must, reliably?
- Data & Analytics – Are we using the data or hoarding dark data?
- UX, Training & Adoption – Do people actually like and use the system?
- Technical Debt & Maintainability – Is this stack getting easier or harder to change?
- Scalability & Future-Proofing – Will this still work at the next stage of growth?
- Accessibility, SEO & LLM Readiness – Can humans and machines find and understand what they need?
- Cost, Licensing & Sprawl – Are we spending wisely or just spending?
- Governance & Ownership – Who is in charge and how do we make decisions?
If you are missing answers in multiple categories, you don’t just have “software” problems, you have operational risk and opportunity sitting in your stack.
Final Thought: Software is Not “Set and Forget”
Owning or using software today (whether SaaS, COTS, niche, legacy, custom, or PWA, etc.) is an ongoing responsibility, not a one-time project.
You need:
- A strategy for how everything fits together
- A champion or partner who owns the application layer
- A roadmap that evolves with the business
- Systems for training, documentation, optimization, and integration
That is exactly the layer Champion1 operates in: acting as the application champion and knowledge backbone for the tools that run your business.
To learn more, chat with us today!
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