Developing A Data Analytics Strategy For Small Businesses And Start-ups
If you’re a small business or start-up, you’re probably reading articles about companies using data science, data analytics, and machine learning to increase their profits and reduce their costs. In fact, Mckinsey just came out with a study that found that the companies they survey could attribute 20% of their bottom line to AI implementations. All those trendy and hyped up words are proving to be effective for companies of all sizes.
As data consultants, we have had the opportunity to help multiple clients in industries like healthcare, insurance, and transportation realize similar gains and cost savings. All of which started with us helping them determine what was the best data strategy for them.
In this article, we wanted to take you through a few of the steps we walk clients through to help them figure out their future data strategy. We hope this article can help you take into consideration what your goals are and perhaps how data can help you achieve those goals in 2021.
Define Where You Are In Your Data Strategy And What Your Data Goals Are
Step one, regardless of how big your company is for our team of data science and software engineering consultants is to figure out where your company is as far as data strategy.
We will ask you questions that help us pin-point how much data do you have on your company’s various workflows, do you already have some data analytics in place, what data tools do you use, etc.
Before we get too deep we need to figure out where we are starting.
Once we have a good scope, our team’s next goal will be to figure out where you want to go.
Do you want to build a dashboard for your small business, how about a machine learning model?
Are you looking to reduce costs? Increase profits? Create a data product?
Even if you don’t know what your data goal is, our team will work with you to understand your needs and help you craft a data analytics strategy.
We don’t expect you to know everything, that’s why our team is there!
But let’s go down one possible path for your 2021 data strategy. Let’s start by saying you just know you want to get more value from your data.
Here are the steps our team of data and software consultants would go down to help you define that value.
Assess What Data You Have
Data is an asset.
This means you need to know what types of data you have to know what you can do with it. The more of your business’s workflows that are stored in databases or third-party tools, the more you can gain from the data.
But it all starts with you figuring out what data you have access to and where is it tracked. Lots of modern tools allow you to pull data from them or at least get an extract through some CSV or Excel report.
Before you can even start to plan your data strategy, you need to know what data you have. Take an inventory, and see if there are valid questions you think you could answer with the data.
Here are a few examples if you are uncertain where that data can come from.
- Salesforce
- Workday
- Asana
- ShipWell
- Trello
- Hubspot
- Zendesk
- Stripe
- Shopify
- Xero
- And more.
Determine How You Want To Store Your Data For Analytics
A common tool for managing data is a data warehouse. This is a central system that acts as a source of truth for your team’s dashboards and reporting needs. These systems do require a general understanding of data modeling, but they are much more approachable nowadays for smaller and medium-sized companies compared to 15 years ago.
So, do you need a data warehouse?
There are a couple of reasons you might consider utilizing a data warehouse for a small company. For example:
- You need to constantly access your data daily for analytical purposes and want to avoid impacting the operations database
- Your data needs to be processed heavily before you can use it for analytical purposes
- You need to develop multiple dashboards that your business will use that update automatically
- You want to have a central place for all your data so you can connect it all
Thanks to AWS and other cloud providers, small business owners, and start-up CEOs can access data warehouse and ETL(extract transform load) technology for a fraction of the cost it has cost larger companies in the past.
This provides a huge advantage to your data strategy. Instead of having multiple technical employees design, develop, and implement a data warehouse. You can pay one data engineering/science consultant. This is because you don’t need to spend time acquiring a server, setting it up on your network, managing licenses, etc. Instead, all of your data warehouse management can be set up on the cloud on a virtual private cloud for your company.
How Can We Help You Use Data To Increase Profits Or Reduce Costs
Just having data in a data warehouse or some central storage location does not create a data strategy. It merely starts to set your team up with an easy place to access your data.
So you need to ask yourself, how will you make your data an asset.
It can provide revenue through the means of creating a product, it can help reduce costs by helping your team spot inefficiencies and it can increase profits by showing possible new tools or solutions you had not considered before.
So how do you go from raw data to actual insights?
This process is a combination of utilizing subject matter experts and data analysts/scientists.
In some cases, you can bring on a data science consultant or analyst and see if they can find cost savings you might have not been aware of.
Here are 4 examples of how our team helped reduce costs and increase profits.
Reducing Costs
Example 1 – Reducing Costs Of Service Cannibalization
Our team, for example, has done some analysis for several companies with little to no guidance and we were able to find optimizations such as when one of our clients had started cannibalizing their services.
This is to say that they had started to add more services over the years to try to increase their profits. However, when we examined their historical data we found that the average users per service were done while the total users had barely changed.
So the business owner was paying more to service the same amount of people.
We found this with no prior knowledge of the owner’s business trends or patterns.
From there, our team was able to work with the owner of the business to reduce market Cannibalization and better optimize their services.
Example 2 – Reducing Fraud Costs
Another approach is to have a more targeted approach. For example, perhaps there is a specific problem in your business you are trying to solve. Such as fraud.
Fraud appears in many industries in many ways. Whether it be healthcare, insurance, or credit cards. Fraud is everywhere.
That being said, often time fraud follows particular patterns.
In healthcare, a common scenario you will see is called upcoding. This is when a healthcare provider bills for a service that is more expensive than the service they provided.
For example, a service provider might claim they provided an emergency or surgical service when all they provided was a standard procedure.
If this happens once or twice, there might be some reasoning behind this. However, if a provider shows higher than normal signs of this behavior, it is likely a sign of fraud.
This might seem obvious now that we have explained it. But just going and telling a data scientist or analyst who has never worked on healthcare fraud before to find fraud, might have them spend days or weeks to come to that conclusion. Instead, you could pair them with fraud analysts (which are common in insurance companies) to help them understand the domain better.
What About Increasing Profits?
Example 3 – Optimizing Pricing
Companies like Uber and Lyft have been optimizing pricing for a long time. The idea of pricing your service based on demand to ensure both you and the customer are getting the highest value is a great way to increase your profits.
We have done a lot of work in the transportation industry, one of the major projects we took on was improving the pricing model for a company that had been manually pricing without considering historical or current demand.
Our team of software and data science consultants helped develop a product that has increased that companies profits by 15%, solely on the model alone. This was done by creating a model that took in past travel data, current reservations as well as possible future local activities(baseball games, fairs, concerts, etc) into consideration.
From there, our team built a simple UI that their team could punch in a date and find an optimized price.
We are now working on integrating that tool into a larger part of this companies infrastructure.
Example 4 – Developing A Data Product
There are companies out there that make 100% of their revenue based on their ability to take data and create insights. These are analytics companies that have developed dashboards and algorithms to help drive insights for other companies.
This may or may not be an opportunity for your company. Many companies will pay to have insights and dashboards pre-delivered to them.
One way you can do this is to find an opportunity for creating a report or dashboard internally inside your company.
If you’re a healthcare company it might be developing a dashboard for fraud detection, if you’re in operations it might be focused on creating a dashboard to help track inefficiencies.
Whatever it may be, you can work to package it and then resell the base of that dashboard to similar companies/teams.
In turn, you now can make money from both your domain knowledge and your data.
Overall, these are just four ways your company can utilize your data to improve your overall company strategy.
What Will Be Your 2021 Data Strategy Roadmap
Next year will be here sooner than we realize. Taking the time as a small business or start-up to plan how you will use data to improve your overall strategy can make a huge difference. Hopefully, this article provides some ideas on where your team can start.
Whether you need to determine what data you have on hand or what you can do with that data, take the time to write a roadmap.
And if your team needs to help to develop a data strategy or road-map for 2021.
Reach out to us today!
If you are interested in reading more about data science or data engineering, then read the articles below.
What Are ETLs and Why You Should Use Them
4 SQL Tips For Data Scientists
What Are The Benefits Of Cloud Data Warehousing And Why You Should Migrate
5 Great Libraries To Manage Big Data With Python
What Is A Data Warehouse And Why Use It
Hiring Data Science Guide – A Guide For Interviewing And Onboarding.
SQL Best Practices — Designing An ETL Video
We really are thankful for you reading our articles. Our team of data science and software consultants enjoy the opportunity to at least hear out your problems. So please feel free to reach out so we can scope out your data roadmap for 202!