Companies don’t care about algorithms…
So why are you trying to “pitch” your data science algorithms?
Do this instead. 🧵
#stats #DataScientists #datascience
So why are you trying to “pitch” your data science algorithms?
Do this instead. 🧵
#stats #DataScientists #datascience
Whether you are trying to get a project approved or sell yourself in a job interview…
Companies don’t want to talk data science.
They want to talk results.
Here’s how to win the conversation.
Companies don’t want to talk data science.
They want to talk results.
Here’s how to win the conversation.
Instead of talking Data Science (and getting stuck in a never ending rabbit hole)…
Try this.
Try this.
Rephrase the business project like this:
1. What’s the business problem?
2. What’s the impact?
3. What’s your process?
4. What’s the expected outcome?
Let me explain.
1. What’s the business problem?
2. What’s the impact?
3. What’s your process?
4. What’s the expected outcome?
Let me explain.
1. What’s the business problem?
When you ask about the business problem, it immediately focuses everyone on their business objectives.
And generally this gets walls to drop in the meeting room…
…Opening all parties up to the goal of the meeting.
When you ask about the business problem, it immediately focuses everyone on their business objectives.
And generally this gets walls to drop in the meeting room…
…Opening all parties up to the goal of the meeting.
And even if you “know” the answer, re-asking the question will help everyone refocus.
That’s important (because I guarantee at least one person isn’t on the same page)
That’s important (because I guarantee at least one person isn’t on the same page)
2. What’s the impact?
Don’t assume you know the real issue.
I almost always get surprised.
Because there’s layers to any problem.
So peel away the layers like an onion 🧅
Don’t assume you know the real issue.
I almost always get surprised.
Because there’s layers to any problem.
So peel away the layers like an onion 🧅
Impact Examples:
- customers unhappy and opting out of a service
- missed opportunities
- wasted time
All of these have opportunity costs.
If a decision could have been made differently, then financially the company would be in a better position.
- customers unhappy and opting out of a service
- missed opportunities
- wasted time
All of these have opportunity costs.
If a decision could have been made differently, then financially the company would be in a better position.
3. What’s your process?
This is where 90% of data scientists screw up.
They dive into algorithms and the data they “need”
Don’t do that.
Do this instead.
This is where 90% of data scientists screw up.
They dive into algorithms and the data they “need”
Don’t do that.
Do this instead.
Show them your process AND where they need to be involved.
1. Understanding the problem financially $$$
2. Getting Data
3. Comparing data to KPIs
4. Identifying Problems
5. Encoding Algorithms
6. Production
7. Reporting Results & Iterating
1. Understanding the problem financially $$$
2. Getting Data
3. Comparing data to KPIs
4. Identifying Problems
5. Encoding Algorithms
6. Production
7. Reporting Results & Iterating
Each step should have a meeting and there should be agreement of the team to move onto the next step.
And notice “algorithms” aren’t even a discussion until Step 5.
That’s because a lot has to happen before you even get to that point.
And notice “algorithms” aren’t even a discussion until Step 5.
That’s because a lot has to happen before you even get to that point.
4. What’s the expected outcome?
Focus on the results that can be expected from this project.
There are no guarantees.
But if successful there are expectations.
Focus on the results that can be expected from this project.
There are no guarantees.
But if successful there are expectations.
Good Examples Of Expectations:
1. Increasing revenue
2. Lowering costs
3. Growing or retaining customers
4. Improving profitability
1. Increasing revenue
2. Lowering costs
3. Growing or retaining customers
4. Improving profitability
If you are reading this and wondering how I actually implement this process in businesses?
And what tools I use to get return on investment ROI for companies?
Or How To Get A Job with Data Science
Then I can help.
And what tools I use to get return on investment ROI for companies?
Or How To Get A Job with Data Science
Then I can help.
I have a free 40-minute training that gives you my blueprint for becoming a 6-figure data scientist.
This free training will cut your journey in half.
It contains the 10 secrets that moved the needle for my career.
learn.business-science.io
This free training will cut your journey in half.
It contains the 10 secrets that moved the needle for my career.
learn.business-science.io
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