From data science and web development to machine learning, the tech industry has never been more competitive. Knowing how to position each team member in your business for success is paramount. So is ensuring continued growth. Having a strategic plan in place for sustainable scaling can mean the difference between success and failure.
1. Improve your skills and offerings.
Take app and web development, for example. While it’s fine to stick with the most popular programming language, it’s a best practice for your web and software developers to diversify their skill sets. Perhaps the best thing a team member can do is to learn an alternative programming language like Python.
While the data structure of Python may seem prohibitive to some, there are plenty of potential clients that would gladly invest in a tech company that offers Python programming. Data science today requires more adaptability and flexibility than recent years as well as a mastery of all data types.
To keep the Python example, say you’re ready to learn the Python programming language. You’ve scoured an Asana community forum to find an online course but you’re struggling to commit. How do you learn Python if you’re unsure where to start? A good place would be a simple Python tutorial. You could capture some of the basics but you’ll probably want a Python course to help you learn Python. You could look for a list of free Python programming courses but the results might be hit or miss.
The best online courses offer a balance of deep learning and cost-effectiveness. Python courses, even free courses, should teach you the fundamentals of Python programming without keeping you in an educational feedback loop.
2. Set better goals.
The OKR methodology can benefit every industry but especially one as reliant on data analysis as tech. OKRs are objectives and key results. They help with goal-setting as well as defining a set of key results. The OKR methodology helps keep your business accountable. One of your key results may even be to have a certain team member learn Python by a specific point in time. All of your goals and key results should be measurable and give you a balanced scorecard of your business’s performance.
The goal of OKRs should be to help you set key results for every use case of your business, whether it’s on the individual level or companywide. Using OKR software can help too and it’s a great idea to try out the methodology of OKRs on a platform with a free trial.
3. Embrace feedback and change.
If something isn’t resonating with clients and customers, why hammer it in? If your data analysis is pointing to product flaws on an individual level, it’s easy to imagine those flaws scaling into something unmanageable. Taking your business to the next level means to embrace the difficult moments and be unafraid of criticism and change. Of course, if the change seems to be too large, it’s always a good idea to rethink it with your team members.
The perfect course of action is to balance intuition, feedback, and the evolving state of data science as a whole. It’s a best practice that will keep you from taking too many unnecessary risks.
4. Be transparent with clients.
Many customers and clients have heard of data science, machine learning, and deep learning, but may need dictionaries to get their precise definitions. As such, it’s your job to be transparent at all turns. Start with your website. Is your privacy policy clear and concise? Do your terms of use make sense for a first-time user? Keep a balanced scorecard of how you fare insofar as transparency is concerned and put your findings to use.
From picking up a new programming language like Python to incorporating the OKR framework to take your goal-setting to the next level, there are plenty of ways to grow your tech business. Simply keep the best interests of your clients and team members in mind. You’ll be surprised at what you can accomplish.
