Unmasking the Hidden Ghosts: The Known and Unknown Costs of Shipping, Churn, and Waste

The other day, I stumbled upon another viral post by Elon Musk, a table that laid the absurdity of unchecked spending or rather data. I couldn’t help but stare at it in disbelief. I thought to myself, “how difficult is it to generate such a report?”. Turns out, very when there is no executive direction and when the top leadership is not asking the right questions. And that’s a problem. This got me thinking about how we deal with inefficiencies in business and government spending.

Whether it’s shipping costs, customer churn, inventory movement or marketing attribution, we’re often haunted by inefficiencies hiding in plain sight. Then, it occurred to me what are the knowns and unknowns that we need to uncover to gain such insights. The Rumsfeld Known-Unknown Matrix is a great way to classify these problems and find ways to eliminate them.

Let me run you by this simple 2x2 matrix.

The Rumsfeld Matrix: Making the Invisible Visible

The matrix breaks down problems into four quadrants:

1. Known Knowns (What we know we know) - High Awareness, High Predictability
2. Known Unknowns (What we know we don’t know) - High Awareness, Low Predictability
3. Unknown Knowns (What we don’t realize we know) - Low Awareness, High Predictability
4. Unknown Unknowns (What we don’t know we don’t know) - Low Awareness, Low Predictability

I have applied this framework to dive into three key areas where hidden inefficiencies quietly drain resources.

1. Shipping Costs: The unseen overhead

Imagine running an e-commerce business where shipping is treated like a sunk cost. It is rarely analyzed, just accepted. But what if I told you that overpaying for expedited shipping or failing to consolidate shipments is like leaving the faucet running in an empty house? For CEOs, CMOs, and data officers, understanding the hidden costs in logistics is the difference between a profitable quarter and unnecessary margin loss.

Known Knowns (High Awareness, High Predictability)

• Standard shipping fees, carrier rates, and fuel surcharges.
• High-volume SKUs that justify bulk shipping discounts.
• Seasonal shipping fluctuations that impact logistics costs.

Known Unknowns (High Awareness, Low Predictability)

• Are we overpaying for expedited shipping unnecessarily?
• Are multiple shipping tools offering the same service but at different rates?
• Are there better-negotiated contracts available with third-party logistics (3PL) providers?

Unknown Knowns (Low Awareness, High Predictability)

• Some SKUs have higher return rates, inflating costs unnoticed.
• Inefficient warehousing locations leading to unnecessarily long shipping routes.
• Consolidating shipments could reduce costs, but teams operate in silos.

Unknown Unknowns (Low Awareness, Low Predictability)

• Ghost shipments—orders that show as shipped but never arrive.
• Carriers charging hidden fees that are buried in bulk invoices.
• Data discrepancies between warehouse inventory and e-commerce platforms.

Businesses often overlook inefficiencies buried in shipping data. A periodic audit and unified data approach ensures shipping costs don’t quietly eat into profits.

Actionable Insight: Conduct a periodic shipping audit and unify data across platforms to expose inefficiencies.

2. Customer Churn: The Hidden Revenue Leak

Think of customer churn like a slow leak in a water pipe—by the time you notice, significant damage has already been done. While executives focus on acquisition, ignoring churn is like continuously filling a bucket with holes in the bottom. A well-structured churn analytics strategy plugs these holes before they become major losses.

Known Knowns (High Awareness, High Predictability)

• Customers with low engagement are more likely to leave.
• Subscription cancellations follow a clear pattern before churning.
• Competitive pricing is a key reason for customer loss.

Known Unknowns (High Awareness, Low Predictability)

• How many customers leave due to poor onboarding?
• Are long support resolution times contributing to churn?
• Are discounts attracting one-time buyers instead of loyal customers?

Unknown Knowns (Low Awareness, High Predictability)

• Some customer cohorts are more profitable than others, but we treat all equally.
• Long-term value (LTV) of churned customers before they left.
• Features that customers engage with most, which could predict churn.

Unknown Unknowns (Low Awareness, Low Predictability)

• Customers who silently stop purchasing but don’t formally cancel.
• Impact of word-of-mouth churn (negative referrals) that go undetected.
• Unseen trends in complaints that never reach leadership.

E-commerce leaders must identify hidden churn patterns, refine engagement strategies, and retain profitable customers instead of throwing money at one-time buyers.

Actionable Insight: Use churn analytics tools and interview churned customers to uncover unknown reasons for leaving.

3. Inventory Management: The Silent Killer of Profitability

Imagine running a grocery store where fresh produce regularly goes bad before it's sold. Inventory management in e-commerce and D2C brands works the same way. If you don’t keep an eye on stocking trends, you'll either be sitting on unsold goods or scrambling to replenish a hot-selling product.

Known Knowns (High Awareness, High Predictability)

• Overstocking leads to increased holding costs.
• Understocking results in lost sales.
• Seasonal demand spikes require proactive planning.

Known Unknowns (High Awareness, Low Predictability)

• Are we accounting for supplier delays in restocking?
• Is excess stock being stored inefficiently?
• Are demand forecasts accurately predicting trends?

Unknown Knowns (Low Awareness, High Predictability)

• Warehouse mismanagement leads to misplaced inventory and unnecessary purchases.
• Some product lines consistently outperform forecasts, but we fail to leverage data insights.
• Discount-driven clearance sales are often not the best strategy for moving excess inventory.

Unknown Unknowns (Low Awareness, Low Predictability)

• Supply chain disruptions affecting inventory beyond just lead times.
• Hidden inefficiencies in inventory tracking software leading to ghost stock.
• Overstocked products expiring or becoming obsolete before being sold.

To maintain stockpiles of essential goods, e-commerce businesses often hold onto slow-moving products far too long, draining working capital.

Actionable Insight: Optimize inventory forecasting with real-time data and AI-driven demand predictions.

4. Marketing Attribution: Tracking What Actually Works

Marketing budgets are often like black holes. Money goes in, but where does the return actually come from? Most CMOs and data officers know they need to track ad spend and engagement, but the real challenge lies in untangling what actually influences a purchase.

Known Knowns (High Awareness, High Predictability)

• Paid ads drive a large share of e-commerce traffic.
• Influencer campaigns boost brand awareness.
• SEO and organic content provide long-term ROI.

Known Unknowns (High Awareness, Low Predictability)

• Are multiple campaigns cannibalizing each other’s effectiveness?
• How many touchpoints does a customer need before converting?
• Are retargeting ads improving conversions or just burning cash?

Unknown Knowns (Low Awareness, High Predictability)

• Word-of-mouth and referral traffic have more impact than measured.
• Attribution models might favor last-click conversions while undervaluing assisted conversions.
• The real ROI of social media engagement often goes unaccounted for.

Unknown Unknowns (Low Awareness, Low Predictability)

• Algorithms affecting ad performance in unpredictable ways.
• Hidden data discrepancies between ad platforms and analytics tools.
• Competitor bidding strategies unknowingly inflating ad costs.

Marketing in D2C is much like government spending in advertising. Both invest heavily in campaigns, yet the true impact is often misunderstood. With proper sentiment attributed to the right channels and numbers, you can capture true consumer influence.

Actionable Insight: Implement a multi-touch attribution model to optimize marketing spend effectively.

Making the Invisible Visible

When I saw that viral post, it wasn’t just funny, it was frustrating. The ghosts draining logistics, customer retention, inventory, and marketing attribution thrive in data silos. Using the Known-Unknown Matrix, we can find the hidden knowns and get closer to the unknowns. This would translate into being able to:

• Cut unnecessary shipping expenses.
• Reduce customer churn by investigating unspoken issues.
• Understand where to spend more vs less.
• Know how much to pile up or reduce.

Data transparency, audits, and cross-functional insights are how we stop these ghosts before they wreck the budget. All this is basic hygiene and a necessity. This just proves again if you are a leader that you don’t have to wait to for a calamity or for the end of the world. Start building a data-first approach now!