Strategic Data Advisory for Mid-Market CPG CEOs

Find and fix the reasons your numbers conflict, your reports can't be trusted, and your decisions carry more risk than they should.

MIT Sloan estimates poor data quality costs companies 15-25% of revenue. For a $30M brand, that's $4.5M-$7.5M a year hiding in the fog of conflicting numbers. (Source: Thomas C. Redman, MIT Sloan Management Review, 2017).

Take the Gold Mine Data Reality Self-Check

~3 minutes | No obligation

Book a Conversation

45 minutes | No obligation

What's Quietly at Stake

When you can't trust the numbers,
all three executive priorities
take the hit at once.

Profit

You can't see clearly what's making money and what's losing money. Margin drivers are hidden. Trade spend ROI stays opaque.

Cost

Your best people are stuck fixing spreadsheets and reconciling reports instead of running the business.

Risk

Forecasts get less believable. Defending your numbers in board meetings and customer reviews gets harder.

The Real Problem Isn't Technology

In most mid-market CPG, manufacturing and packaging companies, the numbers keep conflicting because leaders lack certainty, not systems.

Uncertainty About What Numbers Can Be Trusted

Sales has its pipeline. Operations has its demand view. Finance has its reconciliation. Each system is technically "right" from its own perspective, but together they create noise instead of clarity.

Pattern: when this is fixed, the leadership team stops arguing about which number is real and starts arguing about what to do about it.

Uncertainty About Where Inconsistencies Originate

Supplier data arrives late, incomplete, or in a different format every time. Plants and product lines capture the same facts differently. Definitions and accountability vary by function. Nobody owns the numbers.

Pattern: when source-level ownership is named, downstream cleanup stops being a weekly fire drill.

Uncertainty About What Must Be Fixed First

Before you commit to new platforms, dashboards, or AI - you need to know what actually matters to address first. Otherwise you're spending on what sounds good, not what fixes the real problem.

Pattern: when sequencing is right, you spend on what fixes the real problem instead of what sounds good.

Why CPG, Manufacturing & Packaging Feel This First

Operating between suppliers and customers, data can amplify real risk.

Supplier feeds arrive late, incomplete, or inconsistently structured
Plants, product lines, and systems capture the same facts differently
Customers expect standardized, auditable data on tight timelines
Promotional spending and trade spend move fast - when data doesn't keep pace, margin decisions get made on yesterday's numbers

One flawed file or misaligned definition can jeopardize a relationship that took years to build. This isn't an IT failure. It's an operating reality and a leadership risk.

The Data Reality Conversation

A focused executive conversation to see whether your numbers can support the decisions you're being asked to make.

In 30-45 minutes, we will:

Pinpoint where you feel the most pressure today (margin, growth, AI, or scrutiny from boards/customers)
Surface decisions that are stalling because of conflicting or fragile numbers
Determine whether there's a realistic path to address those issues in terms of timing, ownership, and capacity

From Tim's perspective, this conversation also confirms whether the right decision-maker is involved, the organization is ready to engage, and the team can realistically participate without introducing execution risk.

If the conditions aren't in place, no paid work is proposed. You still leave with a clearer view of where data is affecting Profit, Cost, and Risk.

Book a Conversation

~45 minutes | No obligation

How We Work

Every engagement begins with a conversation, not a contract.
You decide how far things go.

Executive Conversation

No obligation

A structured discussion to understand where margin, growth, and risk feel most exposed, and to confirm that the right decision-makers are in the room.

2-Week Diagnostic

2-3 weeks, paid

A structured executive review that narrows down where decisions are at risk and which issues matter most to address first.

Source-Level Audit

4-6 weeks, paid

A deeper review mapping how your numbers get built - across sources, spreadsheets, and people - to find exactly where they break down.

Executive Sequencing Advisory

Ongoing, paid

Senior-level, tool-agnostic advisory to help you sequence initiatives and evolve the data conditions as you implement changes and explore analytics and AI.

About Tim Brown

Strategic Data Advisor

I help mid-market CPG, manufacturing, and packaging CEOs find and fix the reasons their numbers conflict, their reports can't be trusted, and their decisions carry more risk than they should.

30+ years making sure Finance, Sales, and Operations could read the same number the same way - across US financial institutions, manufacturing, utilities, and entertainment. I've sat at the intersection of business leadership and data operations long enough to know where the real problems live.

I don't sell software or platforms. I help you reach a place where one set of numbers runs the business - where reports agree, decisions move faster, and you stop relying on spreadsheet heroics.

The goal is to show you what must be fixed before you commit to new platforms, dashboards, or AI - so you spend on what matters, not on what sounds good.

My approach is intentionally humans-first. AI is a tool I use, not a service I sell. My experience says the best data work happens when the people closest to the numbers own them - not when a platform tries to do it for them.

30+ years across US financial institutions and manufacturing
Latest role: Wells Fargo (Senior Data Management Consultant)
Focus areas: where the data comes from, who owns it, and whether it can be trusted.
MBA (Marketing Research & Statistics), Ohio State University
BS (Marketing & Economics), Penn State

Connect on LinkedIn

Frequently Asked

How is this different from a business intelligence consultant?

BI consultants build dashboards. I find why your dashboards keep telling you different things in the first place. The work has to happen at the source, not the report.

Why not just hire a data engineer?

A data engineer builds. I diagnose what should be built. Wrong sequence wastes both money and engineering time.

What does "strategic data advisory" actually mean for me?

It means we start with your most pressing decision, work backward to where the numbers are failing you, and produce a plan you can act on. No software sold. No platforms recommended until we know they will work.