In a world where startups are constantly pouring vast amounts of resources into developing their own proprietary tech stack, boAt has distinguished itself by taking a unique approach – i.e. outsourcing its task to multiple tech partners, thereby eliminating the need for an unnecessary overhead burden for the company by developing legacy applications with tech talent. This includes Google, SAP, Shopify and others. 

The company is also betting big on Generative AI. For instance, to improve customer experience management, which includes tasks like intuition, moderation, intent detection, and sentiment analysis, it has partnered with a technology enabler. boAt did not reveal the name due to a confidential agreement, at the time of discussion. 

“We have partnered with a company that already has some of these capabilities, who also happen to be working closely with OpenAI to improve them at a suitable cost and scale,” said Shashwat Singh, CIO at boAt, told AIM, at SAP Now India held in Mumbai last month

However, last week boAt partnered with Amplify.ai and Meta to enhance the personalised conversational experience for its users. This chatbot has been ideated by Meta’s Creative Shop and built in partnership with Amplify.ai. 

At the same time, boAt also has a small but strong research and development team of 35 technologists and data scientists, allowing boAt to maintain a lean and mean organisational structure, who work on product R&D and quality. 

Outsourcing typically involves delegating certain technical tasks such as ABAP or Java scripting development work. However, the overall project and program management, as well as the expertise related to the subject matter and business analysis, are typically kept in-house.

Sailing against the wind 

boAt has its ups and downs. It has been cognizant of scaling its technology stack. For instance, boAt worked with Tally in the earlier days, but it migrated to SAP only a year ago. But why? 

Singh said that SAP offers better feature functionality compared to its competitors, meeting all their requirements. Secondly, SAP had a strong partner ecosystem, enabling them to find more adaptable and flexible Tier 2 or Tier 3 partners. Lastly, the SAP RISE program offered them the flexibility to focus on their core business processes while outsourcing the management of infrastructure and uptime.

Further, he said that Tally lacks a system of stock or inventory management and is primarily focused on accounts, resulting in a lack of integration between inventory and financial systems, making it challenging to assess inventory position. 

Singh said that there were lesser challenges from a product perspective, but the implementation did have its difficulties: challenges in getting the right business processes digitised on SAP, especially when it came to integrating legacy warehousing tools. But, this was resolved by the team instantly. Singh credited SAP’s project management team for helping them with the implementation and keeping track of the progress of the project. 

Why SAP, and not others? 

Singh told AIM that when it comes to scoring correct ERP solutions, SAP stands better than the rest. In boAt’s experience, partner ecosystem and support, as well as feature functionality coverage, are major downfalls for competing ERPs. 

Besides that, SAP’s tech footprint has increased with solutions like SAP EWM and SAP TM. Comparatively, other ERP solutions lack a strong ecosystem and features on the supply chain side. While it may be cheaper in the short term to develop an in-house ERP, it would become more expensive to manage and maintain it in the long run. Eventually, the cost-benefit of off-the-shelf ERP products will be cheaper than doing something else.

Read more: Enterprises Die for Domain Expertise Over New Technologies

Navigating data management challenges 

boAt has already set up a fully functional data lake with SAP data and other data sources, including Google Analytics, Shopify, and unit data. The company intend to traverse the entire information continuum from operational and descriptive reporting to predictive, prescriptive, and insight. It has already gotten all operational reports live on the data lake and are now exploring analytics use cases that can have a direct impact on the top line.

Despite all of these efforts, there exists a dearth of historical data for predictive analysis to work.

“We have limited historical data, which means we are not yet able to utilise predictive or prescriptive insights. Our primary use case would have been demand forecasting, but given that most of our sales come from the popular e-commerce marketplaces which are extremely fluctuating, demand sensing is not effective in that context,” explained Singh. The sales account for close to 80-85%. 

Instead, they are focusing on identifying product gaps by analysing the voice of the consumer to help in the new product introduction process. They don’t require a lot of historical data, but they are focusing on big data and leveraging the voice of the consumer since they don’t get first-party data. Singh aims to transform boAt into an intelligent enterprise that relies on insights and data rather than gut decisions.
In a world where e-commerce giants are gobbling up vast amounts of data, many enterprises like boAt have limited data to work with. Yet, despite this challenge, boAt has carved out a place for itself as the fifth-largest wearable brand in the world.

How did they do it? By taking a unique approach that emphasises marketing and branding besides a significant focus on product R&D and quality.  So if you’re struggling to keep up with the data-driven landscape of modern business, take a page from boAt’s playbook.