Operational decisions are slow because they rely on manual processes and non-automated reporting.
This delay quietly costs time, money, and missed opportunities every week.
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The Problem
- Reports are built manually, often in spreadsheets.
- Key metrics are available only after decisions are already made.
- Teams compensate data delays with intuition and extra work.
- Skilled people spend time assembling data instead of acting on it.
You don’t have a data problem.
You have a decision latency problem.
The Impact
- Operational costs increase silently.
- Errors repeat without feedback loops.
- Opportunities are identified too late to act.
- Automation exists in theory, not in practice.
Data is present.
Action is delayed.
The Outcome
Reduce the time between data and operational decisions.
Not by adding more dashboards.
Not by generating more reports.
By turning existing data into decision-ready, automated workflows.
The Method
Most automation projects fail because they start from technology.
Decision Diagnosis
Decide what actually matters
Identify critical operational decisions and where time is lost between data and action.
Targeted Automation
Automate only what deserves it
Automate only what directly reduces decision latency and operational friction.
Stabilization
Prevent decision decay over time
Monitor, refine, and adapt systems as data and business conditions evolve.
This process deliberately eliminates low-impact decisions before anything is built.
Technology serves decisions.
Not the other way around.
The Offer
Decision Latency Assessment
A focused engagement designed to make decision delays visible and measurable.
Deliverables
- Map of key operational decisions
- Identification of manual and slow decision points
- Estimate of recoverable time and efficiency
- Prioritized automation roadmap
Constraints
- Duration: 2 weeks
- Scope: Fixed
- Outcome: The ability to decide what to automate — and what not to
Proof
Across different operational contexts, these are the patterns we’ve observed. No named clients. No future promises. Only measured outcomes.
Days → Hours
Reporting decisions typically reduced from days to hours.
10–20 hrs/week
Of manual decision-related work eliminated, on average.
1–3 days earlier
Critical signals surfaced before they become problems.
Decision cycles shifted from reactive to proactive.
Typically reduces decision latency by 1–2 orders of magnitude.
About
DagTech was founded as a cohesive network of industry experts, serving those who seek innovation and digital growth.
The team specializes in closing the gap between data and operational decisions — through automation, streamlined reporting, and systems that remove friction where it costs the most.
100+
Clients served between 2023 and 2025
7
Experts in the team, expanding
6.5 yrs
Average experience of the AI and data science team
I work with companies that already have data, but struggle to turn it into timely decisions.
With over 10 years of experience in data systems, automation, and applied machine learning, the focus is not on building models — but on removing decision friction where it actually hurts.
Expectations
This is not a fit if you are looking for:
- Generic data consulting
- Training or workshops
- Dashboards without operational impact
- Hour-based development work
This work is outcome-driven.
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