How SMBs Can Create Better ROI From Their Data Science Team
If you ask any small and medium-sized business (SMB) about its top priority, then their answer, similar to larger companies, typically will revolve around improving customer experience, along with retaining the growing customers as well as increasing revenue. Working with data to bring actionable insights has proven to be the way forward to achieve growth and to stay competitive in the market. However, collecting and storing data is not beneficial unless it can actually drive actionable insights that propel the business forward, and to achieve that creating a data science team for your business is the most crucial step. This data science team can help the businesses in building projects that will be deployed into production for bringing value to their business. However, to derive the maximum output from this data science team businesses must embrace the structures and resources necessary for them to thrive and generate impressive ROIs. Here are some simple steps for businesses to follow, in order to gain maximum profit out of their small data science team. A direct connection with your customers Customer engagement is the key to having a successful business, and therefore businesses must thrive on meeting their customers’ requirements. But, in order to have a better engagement with your customers its always suggested to make them connect to your core team who will be working to resolve your customers’ problem; case in point — your data science team. To enhance your customer engagement, the data science team needs to connect with customers in order to understand their problem and use the same empathy to build specialised solutions for them. Companies can also better interact and engage with their customers by analysing their feedback to improve a product or service. Data sources include traditional in-house data, social media, browser logs, text analytics, and large public data sets can be useful for companies to understand their customers. Jack of all trades The cash crunch is a big issue for small and medium businesses. Therefore the best way to lead forward is to hire people who can multitask in your small organisation and fill the gaps that can be created due to understaffing. Experts suggest to get the maximum ROI; the organisation should create hierarchy and build teams with specificities; however, for SMBs it is more feasible to hire engineers who are more like a jack of all trades. A jack of all trades will have an idea of of the whole business and can provide insights to all the work processes related to engineering and data science. It must be easier for larger companies to have specific employees for each process, but for SMBs it is more important to cover all the positions to get a better view instead of hiring masters and experts at the start. Furthermore, by hiring a jack of all trades, SMBs can familiarise themselves with the necessary programs and software available in the market. Creating a generalised team also increases job satisfaction by creating more exposure for employees. Workplace mentorship is the key Mentorship has always been the key to enhance the productivity of your data science team; however, it can be an expensive affair for SMBS, but completely necessary in this dynamically expanding field. For SMBs to achieve a high-functioning data science team, they can easily rely on workplace mentorship or peer-to-peer mentorship to save the cost of outsourced mentorship. SMBs should arrange workshops and training session inside the organisations where they can open knowledge-sharing by employees and teams. Also, to support such kind of initiatives, SMBS should develop infrastructure. Such initiatives will provide an opportunity for employees to upskill themselves, which in turn will benefit the organisation in a longer run. Collaboration has always been a critical point in order to work efficiently. Also, working together, by sharing insights, will allow your team to tackle more significant problems, leverage individual strengths and avoid depending too much on one person. Identifying Trends For SMBs to survive in this dynamic market, spotting and monitoring trends are imperative. Following behaviours and patterns of the technology and the market will allow companies to take a stab at predicting where the market is heading, or what is the demand of particular products or services that usually changes over time. Often, trend analysis and prediction have been instantiated out of the gut, but with the advent of big data, businesses can now use their data to do the guesswork of the process. Technology has been a dynamic and ever-evolving field and to survive with your small data science team, SMBs need to be aware of the data trends and market information to keep their relevance on. Feedbacks can provide encouragement Lastly, in order to get maximum ROI from your data science team, SMBs should encourage their customers’ to provide constructive feedback to their data science teams to provide encouragement and also to guide them better about their problems. SMBs need to treat their data science team similar to their other departments of the company to create an inclusive environment for data scientists and engineers. Feedbacks not only help data scientists understand their customers’ business but also aid them in creating better solutions for their customers. Making continuous feedback a part of your organisation’s culture will help SMBs to enhance the productivity of their data science team.
If you ask any small and medium-sized business (SMB) about its top priority, then their answer, similar to larger companies, typically will revolve around improving customer experience, along with retaining the growing customers as well as increasing revenue. Working with data to bring actionable insights has proven to be the way forward to achieve growth […]
Here are some simple steps for businesses to follow, in order to gain maximum profit out of their small data science team.
["Data Science", "data science software", "Data Scientist", "SMBs", "SMBs india"]
["big data", "data science", "TPU", "programming_languages:R", "AI", "Data Scientist", "SMBs", "RAG", "ViT", "analytics", "SMBs india", "GAN", "Data Science", "data science software", "R"]
["AI", "data science", "analytics", "RAG", "TPU", "R", "big data", "GAN", "ViT", "programming_languages:R"]
Sejuti currently works as Associate Editor at Analytics India Magazine (AIM). Reach out at sejuti.das@analyticsindiamag.com