MergeYourData.com

According to the Manufacturing Leadership Council, the 3 biggest obstacles for preventing manufacturers from being data driven are:

1️⃣ Lack of systems to capture the data

2️⃣ Data is not easy to access

3️⃣ Lack of skills to analyze data effectively

The surprising thing is that these are the reasons why I started MergeYourData.com in the first place. These were the exact gaps I was seeing and the ones I enjoyed solving the most.

And the coolest part is that each and every rep we get in with a new customer, these top 3 obstacles are solved. We bring the skills from 3, and set up the architecture to solve 1, and then that natively can solve number 2.

To put my money where my mouth is from my last post, if you want a dashboard (or a few) where you can see all your standard marketing metrics like Spend, Leads, Engagement, Sessions for organic, paid, or your website... I'll set that up for you in less than 30 minutes for free.

These tracking and monitoring metrics are low hanging fruit that let you get to the more critical data projects that solve high value problems. They've been built thousands of times across companies and ultimately track the same thing.

I know this just by the last two years working with 50+ companies on data projects.

After thinking a lot about the data & analytics discipline recently, I think solutions that have singular correct ways of doing them should be free or a very low fixed cost.

For example, tracking marketing performance across ad platforms (I'm talking about your standard metrics like ROI, CPC, Spend, etc.). This has been solved many times.

Obviously there are situations where there needs to be some data engineering to prep or blend data. But those are low-value and should be treated as such budget-wise.

The real ROI and higher-investment projects are the ones that are divergent. They start with a singular problem that can't be solved by just looking at ROAS or Margins.

These problems require creative ways of looking at various data sources combined in different ways. These are the real projects worth investing big money in. Not a $50k dashboard to tell you that you spent $500k on Facebook and Google Ads and got 1000 qualified leads.

What's really bothered me over the years with my field (data)... is the feeling of "so what does it really mean/change".

I've been fortunate to have huge projects where the impact is super apparent (millions of dollars saved after identifying ad attribution a vendor was using over years, 100+% growth in revenue 3 months after identifying the highest converting cohorts for a startup).

But also have had many where the solutions are built and they're unused or we look at them and say "so now what"?

And I think it's because some of these projects are ones that are inherently convergent with singular solutions (tracking/monitoring data). While the high value ones are divergent with many potential solutions to a problem (why is this ad platform ROI so low).

I heard the terms CONVERGENT vs. DIVERGENT thinking pop up in a video that was shared with me by Alex Hormozi (bring out the pitchforks 🔱🔥🪧).

It's a common distinction that was coined in the 1950s by a psychologist. And it reminded me of why Data Analytics is misused and hard to get right. Especially in technical organizations like many Manufacturers.

Many engineering problems in manufacturing can be solved with convergent thinking (a singular correct solution to a problem). You know your inputs and your desired outputs. You can tweak some variables to get the desired output.

And that certainly isn't incorrect in any way. It just can be hard to get out of that mindset when you need to.

With data you need convergent thinking to build those dashboards for monitoring things. Things like OTD, revenue, OEE, and other KPIs to keep an eye on.

But to be "data driven" and give high impact analytics, you need to think divergently (coming up with many potentially correct solutions that can be chosen from).

And it's actually a cycle.

1. You use convergent thinking to define a problem. e.g. our OEE is too low
2. You use divergent thinking to get data around Availability, Performance, and Quality. This data gives potential solutions to fix that bad OEE metric.
3. You use convergent thinking to choose the solution that the data suggests gives the best and biggest chance of success.
4. You implement the solution, and use divergent thinking to gather data on all the potential downstream impacts of the change.
5. If it didn't work or something negative and unexpected happened (e.g. Availability improved but Quality dropped), you use convergent thinking to narrow in on the problem again. AKA start back at 1.

If you get stuck at the Convergent thinking stage, you end up asking "so what" when talking data.

Big time savings update... Copy and paste actions between workflows!

Getting tech to align with your operations starts with aligning tech with other tech.

just released this Public Beta for their integration that gives better insights into where and when records synced between the two platforms.

It's one of the most common questions people have with integrations: "When did the data sync? How do I know it's up-to-date?"

And if you're a Netsuite and HubSpot customer who doesn't have an integration setup (or the standard integration didn't live up to expectations)... send me a message!

Manufacturers who are using old CRMs or spreadsheets 😲 to track prospect and customer relationships are sorely missing out on revenue.

I've dug into data from these setups and seen:
- leads that were never contacted back
- meetings that were missed
- opportunities for additional sales that the team didn't see

Modern CRMs make sure this don't happen. Especially HubSpot.

Lead forms should have automated responses and notifications. Meetings should be automatically placed on the calendar of your salesperson. Playbooks should be used based on data you collect so you can identify better fitting services/products, upsells, and cross-sells.

HubSpot provides all this (plus way more). Modern CRMs should provide that. Iff you're not using one and have more than 10 total employees, I can guarantee you're missing out on cold hard cash that should be in your pocket.

Looking for ways to level up your business? Conduct a tech stack audit for seamless operations, tech-savviness, and cost efficiency 🚀

1️⃣ Smooth Operations: Say goodbye to tech roadblocks and streamline your manufacturing processes for smooth sailing.

2️⃣ Ride the Tech Wave: Stay ahead of the game by automating processes and seizing new opportunities.

3️⃣ Save Costs: Evaluate software subscriptions, cut unnecessary expenses, and streamline systems for optimized spending.

Schedule a Tech Stack Audit Demo ➡️ https://buff.ly/3BLPYen

🚨 Exciting news 🚨

Connecting with us to discuss your business goals and strategies has never been easier!

🔹 Ready to move your operations from the 90s to the digital era?
🔹 Tired of your operational capacity not meeting your backlog's demand?
🔹 Frustrated on how to solve software problems with your operations?

We're here to help you! Now you can schedule a consultation with one of our team members to explore if working together is the perfect fit for your business 🤝

Just visit our website ➡️ https://buff.ly/3nmtIUw ➡️ click on "book a strategy call" ➡️ choose the best data & time that fits you!🤩

Get ready to take the first step toward frictionless operations 🚀

How do businesses end up with hundreds (sometimes thousands 🤯) of software subscriptions?

Let's break it down.

Each business function has employees trying to get their job done. Here's a non-complete list of possible business functions for a manufacturer:
- Marketing
- Sales
- CSM/PM
- Engineering/Design
- Production Floor (big broad categorization that varies a lot)
- Shipping and Receiving
- Supply Chain
- Quality + H&S
- Finance
- IT
- HR

That's 11 functions and I'm probably leaving out many more. Now think of 10 people in each of those functions trying to get their job done. That's 110 people with different personal work goals and responsibilities.

They see a problem, they find a software solution that can help (usually without checking what the business already has).

They then get approval to purchase that software. AND ONLY GET APPROVAL FROM THE LOWEST LEVEL NEEDED TO BUY IT.

This is critical because it doesn't allow for an ability to have a cohesive tech stack across the organization.

And that's exactly how you end up with hundreds of software tools.

If you want a free 2-page guide to solve this problem, comment or send me a DM and I'll send it over.