Each year, companies lose $12.9 million on average due to poor data quality. Aside from the impact on the business's financial state, bad data analytics negatively affect decision-making, leading to missed opportunities and inefficient business performance.
Keep reading to discover the main reasons for outsourcing data science, find its main benefits, and learn how to mitigate common outsourcing risks. You will also get best practices for delegating data science to a trusted provider.
Why outsource data science?
High-performing companies are 2.6x more likely to treat data analytics as a powerful asset for securing a competitive advantage in the market, according to Deloitte. Today, companies of all sizes strive to adopt a “data-first” approach to elevate their business strategy with accurate real-time analytics. Data science has turned into a pivotal driver that accelerates business growth.
Data science often utilizes a variety of comprehensive tools, including machine learning, AI, and advanced algorithms to extract meaningful business-related insights from large unstructured data assets. As a result, your business can make more strategic and well-informed decisions, drive innovation, and enhance customer experience. However, to get high-quality insights, you need to secure high-quality input, meaning your data must be error-free and structured to fit for further analysis. This task demands a vast set of skills and expertise and that’s when software outsourcing comes in handy.
With big data outsourcing, you get specialists who will handle the data preparation process, from collection and normalization to labeling and cleaning it up. Next, data scientists build prediction models and uncover general patterns and trends that your business can use to refine its operations and succeed in a highly competitive market. Depending on your needs, you can hire a data science team either to take over your data processing completely or to work on a specific task.
Benefits of data science outsourcing
If you are still hesitant about data science outsourcing, explore the ways it can benefit your business:
Access to a global talent pool
Finding professional data scientists can be challenging as such specialists are in short supply. Data science outsourcing closes this talent gap and provides access to the top-tier experts across the world. This allows you to find data science professionals with specific expertise in your niche that is not easily available within your local talent pool.
Cost-effectiveness
The recruitment process requires a substantial investment of both time and financial resources. Outsourcing data analytics services will save you money as your vendor handles the hiring process, and you don’t need to pay extra for office equipment or employee benefits. Partnering with skilled data scientists locally will cost you considerably more, especially if you demand specific knowledge and skill sets. In contrast, the outsourcing market provides a wide selection of specialists with varying hourly rates to fit your requirements and budget.
Better data quality
With well-vetted data specialists who know how to manage, store, and process large data assets securely, you will gain valuable insights to improve your business strategy. As a result, your company can make prompt data-driven decisions to streamline business processes, allocate resources more efficiently, understand customer behavior, and drive profits.
Advanced technologies
Outsourcing data analytics grants you access to cutting-edge technologies that are available at the moment. Most outsourcing companies leverage the latest tools and innovative techniques to provide better solutions for their clients and be ahead of their competitors. This allows your business to benefit from the world-class software for analyzing, structuring and visualizing data without substantial investments to cover licensing fees.
Improved scalability
Flexibility is one of the top business priorities, and outsourcing enables easy scale-ups and scale downs depending on your scope of work. As your business grows, so do your datasets, and your in-house team may be unable to handle the work volume without external support. Outsourcing work related to data analytics can support the expansion of your team, speed up development processes, while also offering the flexibility to change the number of experts after the job is done.
Risks of data science outsourcing
Data science outsourcing also comes with some risks that can negatively impact your business. Gladly, there are ways to avoid them and benefit from data science and analytics to the fullest. Let’s discover the most widespread risks below:
Security issues
The possibility of security risks is increasing, especially when you delegate data science tasks with sensitive information to a third-party vendor. Yet, this risk can be easily avoided by ensuring your data science provider has all security compliances in place. Ensure that your outsourcing partner holds ISO 9001:2015 and ISO 27001:2013 certifications, which confirm that they apply the best security practices to protect customer data and provide the highest quality control. When signing a contract, be sure to document all the security measures your service provider must follow and the legal and financial consequences for non-compliance.
Miscommunication
Working with third-party vendors can result in miscommunication issues and impact the results of your project. This problem arises from the lack of realistic scope of work with defined deliverables and deadlines. To keep your team aligned with your objectives, establish clear expectations right from the start. Write detailed requirements documentation and set up regular meetings with the data science team to mitigate any misunderstandings and check their progress.
How to successfully outsource data science to a reliable partner?
Looking for a reliable data science outsourcing provider is quite a challenge; however, with our best practices, this process can be easier to navigate:
Define your needs
Before searching for a reliable vendor, identify what gaps in your business you aim to address through data science outsourcing. Once you determine areas that demand improvement, you can outline a detailed scope of work by specifying the exact tasks you need to cover. Define your expectations regarding deliverables, deadlines, and budget. Having a clear scope will help you better understand what expertise and skills you require from your data science services provider. If you still hesitate on where to begin with your business needs and requirements, make sure your vendor provides a solution discovery service and request it to get your project requirements right from the start.
Research the providers
When you clearly understand your needs, you can conduct thorough provider research. Take a look at our short guide on selecting a reliable data science services provider for your project:
- Explore platforms like Clutch and GoodFirms to search for the top data science companies and check their reputations based on client testimonials.
- Check potential providers' websites to assess whether they have the required domain knowledge and industry-recognized certifications. Also, remember to review their case studies to ensure their experience with projects like yours.
- From the extensive list of companies, narrow down the best ones and contact them to share your project’s ideas. Be sure to ask about data collection and processing methods and procedures to ensure the highest standards of security and quality.
- After discussing all the cooperation details, choose one provider to outsource data science that matches your requirements and budget.
Establish a clear cooperation agreement
The cooperation agreement is a key stage that will determine the success of your project. Specify all project details – key milestones, defined deadlines, security measures, and legal requirements. Make sure to select the appropriate cooperation model that best suits your project, as the payment terms and collaboration conditions depend on it.
Include in the agreement the communication channels and a clear division of responsibilities to ensure smooth workflow. A cooperation agreement safeguards your business against miscommunication and security issues that can negatively affect your company’s operations and brand reputation.
Lemberg Solutions’ expertise in data science
Lemberg Solutions has an ideal match of skill sets and expertise with our senior-level specialists who hold Ph.D.s in data science. We have been providing first-class solutions for companies specializing in healthcare, industrial IoT and manufacturing, energy, e-commerce, and agriculture for over 15 years. Discover the success stories of our clients who entrusted us with their data science projects:
Computer vision-based solution for Barkom Ltd
Barkom Ltd, an agricultural company specializing in breeding pigs and cattle, requested to automate the process of monitoring pigs’ weight. A major obstacle was the insufficient amount of training data, so our specialists created a hardware solution to collect data, based on which they developed a weight recognition algorithm. With non-iterative neural networks and a tailored image recognition algorithm, our team developed a computer vision-based prototype that accelerates the weight monitoring process with 98% recognition accuracy.
ML-based motion detection and classification system for Boxx+
Boxx+, a startup offering a workout app for boxing enthusiasts, wanted to build a solution for detecting and classifying punches to enhance the boxing routine of their end users. To build a highly accurate model, our data science experts collected a dataset by analyzing how different users performed all punch types. We trained the model with the gathered data and integrated it into SDKs. As a result, our client got an innovative model for their users to level up their boxing activity.
Algorithm and firmware development for FHCS
Freudenberg Home and Cleaning Solutions (FHCS), a company specializing in cleaning products and systems, needed help implementing new functionality by incorporating a unique algorithm. Our data science experts analyzed the data provided by FHCS and built an algorithm to provide users with instructions based on real-time data. Our embedded engineers successfully implemented the algorithms into the firmware solution, thus enhancing the customer experience.
Conclusion
Data is the backbone of business success, and to get the most value from it, you need to leverage data science potential. A data-driven approach is not a fancy trend but a demand for modern companies to stay relevant in the highly competitive market. Although data science outsourcing provides numerous benefits, it also comes with certain risks. However, with a reliable data science services provider, you don’t need to worry about them. A trustworthy outsourcing company can transform your business operations and propel innovative solutions – all based on advanced analytics. Reach out to discuss your data science needs!