Data Analytics Vol. 2: Thinking Like the Machines
Welcome to the second installment of our ongoing series with data analytics, the key to business success in the post-modern world. In our previous article, we explored how data analytics have revolutionized small businesses, empowering us to ditch the guesswork of the past in exchange for concrete facts and educated analysis. We then went over the four types of data analytics—descriptive, diagnostic, predictive, and prescriptive—to navigate the present and future of commerce with precision. With the help of Dr. Gabrielle Pogge, a data analyst with a PhD in social psychology, we discovered that data analytics are new cornerstones for understanding market trends and customer behaviors, thereby propelling small businesses forward.
Where do I even start?
“But I’m not a statistician, and I don’t have the resources to pay one. This can’t work for me.”
Calm down, chief. Have a toke; there’s hope for you yet.
Most of us skipped as many math classes as our creativity allowed. We’d probably rather pull out a molar than try to write a line of code to analyze data. So, we asked Dr. Pogge, besides using the force, what can small business owners realistically do to leverage the power of data?
“Two things you can do—today—and with little to no cost, are to begin cultivating a data-driven culture within your small business, and to think carefully about whether your current business processes support data-driven decision making. If you want to be able to access and have confidence in the data that will be most useful for converting insights into actions, you need to intentionally design your business processes to support data quality. Data are only as useful as they are reliable—and making decisions based on unreliable data can ultimately harm your business.”
Two things you can do—today—and with little to no cost, are to begin cultivating a data-driven culture within your small business, and to think carefully about whether your current business processes support data-driven decision making. If you want to be able to access and have confidence in the data that will be most useful for converting insights into actions, you need to intentionally design your business processes to support data quality. Data are only as useful as they are reliable—and making decisions based on unreliable data can ultimately harm your business.
Grow a Data-Driven Culture
Here are 5 simple things you can start doing right now to embed analytics into your business core (yep; don’t skip leg day, but it’s really all about the core):
Define Clear Objectives
Identify specific, achievable goals for using data analytics. This might include improving product stock management, optimizing marketing strategies, or enhancing customer experiences. Clear objectives help to focus data collection and analysis efforts. Not sure what your primary objective should be? Identify your biggest problem and go from there. That’s the whole point.
Educate and Train Your Staff
Invest in training for your team. Understanding the basics of data analytics and its relevance to their roles can encourage staff to actively participate in data-driven initiatives. This could involve workshops, online courses, or hiring a consultant to provide initial training.
Implement User-Friendly Tools
Utilize data analytics tools that are accessible and understandable. For small and medium businesses, it’s important to choose software that doesn’t require advanced technical skills. Tools like Google Analytics, Tableau, Excel or Microsoft Power BI can be good starting points.
Collect Relevant Data
Identify which data points are most relevant to your business objectives and how to get them. This might include sales data, customer feedback, website traffic, or social media engagement. Use your objectives as a guide to avoid getting overwhelmed by irrelevant data. Keep it lean.
Encourage a Test-And-Learn Approach
Promote a culture where experimentation is encouraged. Use data to make informed hypotheses about operations or marketing, test these hypotheses, and analyze the results. This approach helps in understanding what works and what doesn’t.
Design Business Processes That Safeguard Data Quality
Now that you have the right strategy, it is time to rewire that mindset and start thinking like a black belt data ninja to protect that precious data:
Implement Clear Data Entry Standards
Establish and enforce clear guidelines for data entry. This includes standardizing formats for dates, monetary values, and customer information. Having everyone follow the same format reduces errors and inconsistencies.
Automate Data Collection Where Possible
Implement automated systems for data collection to minimize human error. For example, use Point of Sale (POS) systems that directly integrate sales data into your inventory and accounting software.
Feedback Loop Error Correction
Create a system where employees can easily report any data inaccuracies they encounter. Quick correction of errors prevents them from affecting downstream processes.
Use Reliable and Compliant Software
Choose software tools that are known for data accuracy and are compliant with industry regulations. Make sure these tools are regularly updated and maintained.
Plan for Data Redundancy and Back Up
Ensure that there are backup systems in place to prevent data loss. Regular backups and redundancy measures protect against data loss due to hardware failures, cyber-attacks, or other unforeseen events, or simply you forgetting to plug your laptop or save that spreadsheet… I mean, we didn’t tell you data nerds don’t partake on occasion.
Coming in April:
Volume 3: The Datanamics
STAY TUNED!
