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You’re late for digital transformation
We’ve already talked about how digitization isn’t just about having an app for everything.
It’s about optimizing processes with technology.
Where to start without dying in the attempt (or in the attempt to hire the cheapest option)?
Here are some practical steps to help you overcome your laziness:
1️⃣ Make a diagnosis:
Which processes are manual or inefficient? (Sales, inventory, customer communication, document management, etc.).
Where do you lose the most time or money?
2️⃣ Identify tools:
Look for solutions (many are free or inexpensive to start with) for those weak points.
Do you need to manage customers? A basic CRM.
Share files? The cloud (Drive, OneDrive).
Sell online? A Facebook store or a marketplace (Mercado Libre).
Fast communication? WhatsApp Business.
3️⃣ Start small (Digital MVP):
Don’t digitize everything at once. Choose 1 or 2 processes, implement the tool, test, adjust.
Example: record sales in a shared Google Sheet.
4️⃣ Train your team (or learn yourself!):
The best tool is useless if no one knows how to use it.
Invest time in teaching. There are thousands of free tutorials online.
5️⃣ Measure and adjust:
Did the change work? Did it save time? Did sales increase on that channel?
Use the statistics provided by the platforms themselves (Google Analytics, network insights).
Digitization is not magic, it is work and adaptation.
But it gives you control, saves you costs in the long run, and opens doors to new customers.
Stop procrastinating and start TODAY.
hashtag#digitization hashtag#SMEs hashtag#business hashtag#productivity hashtag#digitaltools hashtag#management hashtag#entrepreneurship hashtag#stepbystep
All in one Data scientist?, HR fail
I see job offers asking for a “jack of all trades” in Data Science. Someone who knows everything: Data Engineer, Analyst, Scientist, and even Machine Learning Engineer.
Really? 🤦♂️ (It’s not just multipurpose positions in marketing anymore.)
Data science is a field with specialized roles, each with its own skills and tools:
📊 Data Engineer: Cleans, transforms, and moves large volumes of data. Think rivers and seas of information. Needs Spark, Hadoop, SQL, Clouds…
📈 Data Analyst: Translates that data into business language, creates visualizations, tells the story behind the numbers. Needs Python, SQL, Tableau, Power BI, and communication skills!
🔬 Data Scientist: Explore data, create predictive models, look for hidden patterns. You need Python, scikit-learn, TensorFlow, statistics…
🤖 Machine Learning Engineer: Build, optimize, and implement those models in systems and applications. You need Python, JS, APIs, Cloud…
Asking one person to do all that for a basic salary is to understand NOTHING about what is needed (the only thing missing is for them to ask you to pay for their cloud server).
It’s like asking a single doctor to be a surgeon, cardiologist, pediatrician, and radiologist all at the same time.
If you are an entrepreneur, be clear about what you need and hire the right specialist (or team).
If you’re a professional, don’t sell yourself as a “jack of all trades” if you’re not (and if you are, charge accordingly!).
Let’s stop burning professions to save a few bucks.
#datascience #bigdata #analytics #employment #hr #specialization #jackoftalltrades
Building B2B trust.
I have been on both sides of the table: as a digital service provider and as a customer looking for solutions.
And I see recurring patterns:
🤝 The Provider:
– Promises “guaranteed” and “fast” results (sells smoke).
– Is not transparent about processes or actual costs (overcharges or “ties” the customer).
– Does not provide access to platforms (domain, hosting, ad accounts) when the contract ends.
– Does not train the customer to manage their own tools.
– Focuses only on selling, not on providing good after-sales service.
😟 The Customer:
– Always looks for the cheapest option (“the nephew” or the agency that gives it away for free).
– Is unclear about their business objectives (wants “more sales” without knowing how much or how).
– Does not invest time or money in learning or training their team.
– Expects immediate results without understanding the process.
– Does not provide the necessary information to the supplier (photos, catalogs, etc.).
The result: frustration, loss of money, and mistrust in the digital world.
The key is clear communication, transparency (from both the supplier and the customer), setting realistic expectations, and understanding that this is a partnership.
The supplier provides knowledge and execution; the customer provides clear and transparent business information; between the two, there is commitment.
#business #suppliers #customers #digitalmarketing #webdevelopment #transparency #expectations #collaboration
My Clients
These are my latest customers, but in 8 years I worked with almost 400 brands, from small to big companies.
