This is a series of posts detailing data points and experiments to eliminate the risk of losing money while manufacturing spend for cash back and travel rewards. The result of these experiments will be a tracking tool for manufactured spend from credit card purchase to liquidation (of cash equivalents or goods).
We left off in the last post
talking about the difference between a process and tool. To test the theory that we should be process focused instead of tool focused when solving the problem of tracking manufactured spend, let’s run through 2 scenarios:
Scenario 1 – a tool focused conversation about gift card reselling:
You: I have a lot of gift cards and I need a way to track them.
Me: I have this manual gift card tracking app. Just enter in all the details of each card!
You: Well actually I buy so many gift cards each month copying and pasting is painful.
Me: Oh ok. Use this magnetic stripe card reader to get the card number into your spreadsheet faster.
You: That doesn’t me with help the electronic ones.
Me: Oh ok. This reads your email and will enter in the e-cards.
You: Great but that doesn’t tell me the balance on each card!
Me: Oh ok. Here’s another tool that will check the balance and update your spreadsheet. Also this was a super conversation – let’s be best friends!
Scenario 2 – process focused conversation
You: At a high level, I do this every time I buy a gift card:
1. I watch for gift card deals err day every day.
2. Use a shopping portal to get cash back or buy in-store.
4. Update spreadsheet
5. Sell them online.
6. Update spreadsheet
7. Check for cash back payout
8. Update spreadsheet
9. File all gift cards and receipt
Me: Based on your current process you need a tool:
1. designed for a high volume transactions, that’s simple and quick to get in an out of.
2. to minimize your repetitive tasks – most likely data entry – as much as possible.
3. allows for multiple transaction types or gift card sources
4. allows for standardization like the ability to create templates (i.e. limiting repetitive administrative tasks).
5. Built-in audit process for cost of goods sold (e.g. cash portal, shipping, etc) and sales so you don’t lose any profit margin
6. Cloud based document archive system.
You: Yes! Develop this for me please! Here’s all my cash.
Hopefully the scenarios came across as a lighthearted way to show that focusing on the process to define our requirements is a more efficient and effective way of picking our tool(s). Tools should complement and support your process. If you build your process around existing tools, you’ll sub-optimize.
Your process will be built with hidden inefficiencies causing slowness, errors and increased risk of losing money. Now that we know this is a process problem we can brainstorm some hypotheses around why our processes are breaking. Because we’re always either increasing the complexity or volume of MSing, we’re putting greater demand and stress on our tracking process.
We’re demanding more goes through the process (i.e. throughput
) and we want the speed and accuracy to stay consistent. We have these expectations but we aren’t doing anything to strengthen the process to handle the increased stress. There are many tools used in lean/process improvement to strengthen processes but they all use PDCA
(plan, do, check, act).
Like any good lean/process improvement person, I’m going to set up a problem by establishing quantifiable data points. Why?
Because data doesn’t lie! Because I’m still gathering data from our community, I’ve set up my own data points as a starting point. If you have 5 minutes you can add your data
and get a chance to win a free lifetime subscription to the MS tracking tool!
I tracked my credit card sign up bonuses via memory. In April 2015, I lost track of 3 credit card minimum spend bonuses, due date and my required amounts. I created a spreadsheet to sign up bonuses.
Two months later, my company switched to a mandatory corporate card so I wasn’t able to use my corporate travel expense. With these variables changing, I added complexity to my travel hacking process by manufacturing spend.
Within 30 days I manufactured spend (MSed) from $0 to $5k using Redbird as my liquidation method and purchasing Visa gift cards (vgcs) in store. The next month I increased my MS volume from $5k to $15k using the same method above but adding 2 Redbirds and purchasing vgcs online. Currently I do ~$30k per month using One VIP Serves
, money orders (MOs), Amazon FBA
and bill paying for others. Let’s simplify!
We want to take our qualitative statements to quantitative statements. By doing this we accomplish two things –
- if we can get our problem into quantifiable data then we can study it by gathering more data points.
- we can create actionable metrics or KPIs to show that we’re solving or problem
Qualitative: The beginning and end points of my MSing process is from using my credit card to buy cash equivalents or real goods to liquidated cash available to pay off my credit card. Whether buying vgcs, MOs, paying bills for others or buying inventory to sell via Amazon FBA, I don’t know where my money is at all points in the process while manufacturing spend. Why is this a problem? If i don’t know where my cash is at all times then there’s a chance I’m losing it somewhere.
Qualitative but simplified: I want to know where my money is while MSing from using my credit card to buy cash equivalents or actual goods to liquidated cash available to pay off my credit card. Said another way, I don’t want to lose track of any money while MSing.
Quantitative: My ideal state is that I have $0 lost in tracking process. My current state is year to date, I’ve lost track of $3300 somewhere in my tracking process at various points in time. This means I have a problem which I can quantify as $3300 (ideal state minus current state).
I made you a pie! (chart)…
This is just one example. I’ve heard many similar stories from other MSers who were kind enough to share with me and humble enough to value learning from their mistakes more than their own ego. Here are just a couple:
I’m sure you have your own data points similar to the ones above. This doesn’t have to be limited to cash equivalents either! We could easily replace the information above with goods you’re reselling via Amazon FBA. Amazon is notorious for losing packages or breaking them.
They also don’t care much about letting you know so unless you’re viewing your inventory reports for random adjustments or auditing your inventory from inbound shipment to sold you may not notice. Since your inventory is just MSed cash which you need to pay off your MSed debt on your credit card, you may find this a bit annoying.
Gift cards, money orders and Apple watches are just vehicles for MSing. This means we need a tracking system that can handle CEs and inventory MSing.
What Can You Expect Next?
- Post #1 – Why you’re losing money manufacturing spend
- Post #2 – Process vs tool analysis: Why you’re focusing on the wrong one
- Post #3 – Manufactured Spend Tracking: Problem Statement (current post)
- Gather data to find statistical correlation between the following attributes:
- At what level of gift card, money order purchasing does our risk increase?
- At what level of MSing does our risk increase?
- What are the chances we’re losing money at each level?
- What $ or % range are we losing?
- What are the most common variables that increase our risk? Are there contingency plans?
- Capture more case studies to illustrate the full list of variables or risk we exposure ourselves to so we can create contingency plans
- Review and analysis about why these 20 tools don’t work for the MSing or reselling process:
- gift card trackers
- smart cards
- various other tools – spreadsheets, memory, backpacks
- What MSers and small business owners have in common
- What MSers and agile software development have in common
- Put solution through the following stress tests:
- Amazon FBA reselling
- GC reselling
- MSing ranging from $30k – $500k
- Ongoing posts – Adjust prototype and develop final solution for MSing based on community feedback and MSing experiments
Add Your Data – WIN A MS TRACKER FOR LIFE!
Image Source: blog.ssqi.com