Google Sheets vs IBM Targetprocess: Complete Comparison (2026)

G

Why choose Google Sheets

• Higher Cost score (9/10 vs 4/10)
• Higher Ease of Use score (8/10 vs 5/10)
• Better fit for freelancers (8/10 vs 1/10)
• Better fit for small business (7/10 vs 3/10)

Why choose IBM Targetprocess

• Higher Scalability score (9/10 vs 4/10)
• Higher Analytics score (7/10 vs 6/10)
• Better fit for enterprise (9/10 vs 4/10)
• Includes Kanban boards, which Google Sheets lacks

G

Google Sheets

Pros

• Real-time co-editing, comments and version history make it easy for a team to share one tracker.
• Prebuilt project management and event-planning templates mean teams do not have to build a tracker from scratch.
• There is no extra cost for organisations that already pay for Google Workspace seats.
• Connected Sheets can analyse BigQuery or Looker data with billions of rows directly in a spreadsheet.
• On higher Workspace tiers, Gemini can create trackers and write formulas from plain-language prompts.

Cons

• It has no native Gantt charts, task dependencies or time tracking for real project scheduling.
• Missed deadlines do not trigger automatic alerts, so team members have to be notified by hand.
• Large or complex shared sheets slow down and are easy to break when several people edit at once.
• Timeline view is limited to certain paid Workspace editions.
• Dashboards and reporting have to be built by hand or added with add-ons.

IBM Targetprocess

Pros

• Highly configurable boards, workflows and views, which reviewers repeatedly credit as its main strength.
• Connects team-level work to strategic objectives and investment decisions, which most task-focused project tools cannot do.
• Supports Scrum, Kanban, SAFe and traditional methods side by side, which helps organisations in transition.
• Works as a portfolio layer over Jira and Azure DevOps, so delivery teams can keep their existing tools.
• Analyst recognition, including a Strong Performer rating in The Forrester Wave for Strategic Portfolio Management Tools, Q2 2026.

Cons

• Reviewers report a steep learning curve and difficult initial setup and navigation.
• No public pricing, and comparison articles say it is costly for small teams.
• Forecasting and burndown accuracy depend on heavy, disciplined data entry.
• Some users report limited integrations beyond the core tools, and say moving or exporting data takes manual effort.