A key turning point in a startup’s Analytics journey is when it has a data pipeline in place, but lacks processes for reproducible analysis, scaling up models and performing experiments. This is when they need a data custodian, to help them succeed TODAY while setting them up to be data-driven TOMORROW.
At this stage, it is often tempting to try handling data requirements in-house. Yet, with their hands always full, startups are often unable to fully utilize the power of data they collect. When utilized to its full potential, Data Science can be a great competitive advantage for businesses — uncovering hidden opportunities, identifying trends and patterns, pinpointing problem areas and successes — all resulting in rapid -growth; the ultimate goal of start-ups.
Instead, by delegating this area to a trusted partner, startups can access industry knowledge, perform advanced analytics and generate valuable business insights; while saving time and capital. Here’s how:
Access a wider mix of knowledge and talent worldwide
Sourcing data science professionals with the right skills and expertise is always time-consuming and expensive. Since data science projects are strategic by nature, finding the right fit is important to power real business growth. Outsourcing provides access to a ready pool of analytics ‘ninjas’, with cross-industry experience.
Re-allocate capital where it is most required
Lean startups need to keep their overheads low; while focussing on customer acquisition. Early-stage startups can reduce Analytics costs by up to 90% — savings that can be better utilized for other purposes.
Re-allocate core team’s attention on things that really matter
Since the partner has requisite tools and skillsets to help a startup achieve its data science goals; key team members save bandwidth. Instead of fussing over data-related issues, they can focus on functions like customer service, outreach, marketing — all of which provide significant head start over competition.
Access latest tech stack
Outsourced teams bring methodologies and tech stack that position data science projects for success. With their expertise of deploying tech across industries, they can enable startups come up with innovative ways of drawing insights from data.
Professional data management
Agencies that provide advanced services are usually skilled at handling clients’ enterprise data. They are well-versed with handling sensitive data and implement safe, responsible technical and physical controls that are designed to prevent unauthorized access to or disclosure of enterprise data. Lean startups are lean because they aren’t bloated with unnecessary costs, slow tech and inadequate talent. Finding an Analytics partner equips startups with much-desired speed and flexibility, by offering high-quality, tailored data science solutions.
So, how does one identify a trusted, reliable Data Science partner?
If you’re still reading this, your next question would be — How do I go about choosing an Analytics partner?
Finding the ‘right fit’ can be tricky yet worth the effort. Teaming up with an experienced partner can help ensure that your Analytics charter is well taken care of and will bring you the insights you require, to fully leverage data you collect. Here are 3 common stumbling blocks to expect, when evaluating partners:
Remember, no two startups are the same. What works for others might not work for you. To continue the conversation, reach us at quickresponse@thinkbumblebee.com.