From Fortune 500 companies to medium-sized enterprises, embracing digital transformation has led to data becoming the new currency. The ingestion of data as a result of daily business processes has skyrocketed over the past few years.
In this data-driven environment, robust analytics can offer a competitive edge to businesses. However, many organizations lack the experience and the know-how to build a talented analytics team needed to analyze all the data they generate. It is an expensive and time-consuming process that involves recruiting experts, acquiring tools and technology, identifying use cases, and so on. The scarcity of required talent in the market and a lack of understanding about analytics best practices within the teams further complicates it.
This is where Analytics Outsourcing comes in. It enables organizations with contextual domain expertise and skilled labor in a fast and, cost-effective manner.
Data Analytics Outsourcing is a simple model of cooperation where a company trusts an analytics service provider with its data and receives actionable insights. And to make the deal sweeter, it is the analytics service provider who handles everything from infrastructure set-up and maintenance to data management and analysis, depending on the analytics maturity of the company.
Roughly there are four types of analytics and insights providers based on their core competencies:
To understand how outsourced data analytics can help your business, I feel it is essential to take a step back and figure out why your business needs to outsource its analytics requirements.
The following are a few benefits to consider:
Outsourcing offers you the advantage of getting the exact data science skill-set needed for your industry. Analysts often work in the same industry for an extended period of time, gathering valuable insights that are very specific to the industry. Insights that can help you better shape your products or services and provide a better customer experience. If you are in the e-commerce industry, you will be able to outsource your Customer Experience Analytics requirements from a vendor who specializes in CX Analytics alone. Working in a niche field, the vendor will have deep industry knowledge that your brand can greatly benefit from.
With a high demand for quality data analysts, there are few eligible candidates that you can access and vet for the position. Moreover, the hiring, onboarding and training of employees is a resource and time-consuming process. Analysts with niche skill sets are even harder to employ and afford. You can simply outsource your data to a service provider who can support your business immediately with analytics consulting, talented data scientists, skilled analysts, and machine learning experts. Why employ expensive personnel, when you can outsource their services and save resources?
SMEs and even large organizations do not always have the manpower or the bandwidth to carry out time-intensive market research and analytics tasks while ignoring other business processes. Analytics outsourcing offers you flexibility, freeing up core-employee bandwidth which can be dedicated to other facets of the business which need attention.
Companies handling their own data analytics requirements are often the victim of unintentional non-compliance with security regulations. You never have to worry about sticking to regulations such as General Data Protection Regulations (GDPR) if you outsource your analytics requirements. Professional analysts know the regulations well and can help you avoid the common pitfalls while providing you with error-free insights.
Effective data analytics is crucial to customer-centric businesses, especially in a B2C enterprise. Analytics is key to understanding your customers through their data, and leveraging the insights to anticipate their needs, enhance your products, better your services, and improve the overall customer journey. Why depend on an in-house survey, when outsourcing can enable you to analyze a million clients every time they engage with your brand across channels?
Last but not the least, the entire process from talent acquisition and onboarding to training and full-time employment, along with providing the necessary hardware and software required for efficient data analytics, demands time and resources. Every resource employed costs money, and in today’s fast-paced economy, even time is money. Your organization can save all costs associated with employing data scientists and analysts for an in-house analytics ecosystem, by simply outsourcing analysts at a regularized fee.
Analytics Outsourcing is the key to your business minimizing cost and effort while maximizing the revenue being generated. And to make the deal sweeter, it is the analytics service provider who has to handle everything from infrastructure setup and maintenance to data management and analysis depending on the analytics maturity of the company.
Depending on the requirement, your business can engage with an external service provider for bespoke solutions, who takes all the responsibilities, respects your data privacy policies, and delivers error-free actionable insights.
Here are a few popular engagement models offered by analytics vendors:
This is a time-bound engagement model, that helps a company access the technical knowledge and the domain expertise from an outsourcing partner for specific projects. It helps the company minimize costs and manage time, and is effective when there are only minor updates during development.
Companies aiming for digital transformation and attempting to build their in-house team will often opt for this engagement model during the initial period. But as it is project-based and the vendor charges for every resource, it ends up being a costly initiative. As a company’s analytics matures, they would rather select staff augmentation as the next step toward enhancing capabilities.
A straightforward model that enables a company to supplement its existing or growing in-house analytics team, with an external team from an outsourcing vendor. For example, if your company needs help with data engineering for a large project, you can augment your existing data engineering capabilities with additional data engineers.
This can be a temporary model to support current requirements or a long-term engagement with the outsourcing partner. Engagement models such as this, usually work best when the organization has a mature analytics culture to support seamless integration of the external resources.
A model which offers considerable flexibility, as the company specifies the requirements through a statement of work, and the outsourcing partner provides the analytics support, manages the offshore or external staff, and holds responsibility for delivering the project.
The company does not need to make investments for in-house analytics capabilities, and the managed services offer a defined analytics structure which is both scalable and cost-effective. This can also be viewed as a tactical consultancy model, where the client outsources the domain and technical expertise that is lacking internally.
This engagement model involves the outsourcing partner building the analytics solution for the client, operating alongside the client, and transferring to the client. To put it simply, a company can complement its team with resources from a vendor, enable the in-house and external resources to operate in an integrated environment, and then incorporate the external resources into its payroll.
The company benefits from the outsourced expertise and benefits further by absorbing the resources and adding to its analytics maturity.
A company can partner with the outsourcing vendor to develop a center for analytics excellence, where both teams can collaborate seamlessly. This model promotes smoother cooperation between IT and business teams, enables better data management, fosters the adoption of new BI tools, and ensures high-quality business intelligence at an optimal cost.
This is an engagement model where the analytics vendor provides its services considering its client’s time zone and their proximity. This enables the vendor to integrate with the client’s in-house team, coordinate seamlessly, and set up a 24×7 operating model. This enables both parties to optimally utilize resources and enables the vendor to deliver on the client’s requirements at speed. This has been a prominent engagement model for IT consulting services.
It is natural to have certain questions and concerns when your organization is opting for analytics outsourcing partners, such as the security of your data and which service provider will be ideal. The following are some common concerns that keep recurring and are questions that you may have as well.
While choosing the ideal service provider for analytics outsourcing, always check the vendor’s expertise, their partnerships, and certificates. While examining the vendor’s portfolio, keep a lookout for projects pertaining to your industry. A vendor with enough experience in your industry will be able to offer invaluable insights to boost your business. You should also pay attention to other aspects such as speaking the same language, coordinating during working hours, a proactive approach to analytics, and efficient conflict resolution. All these add up to the overall quality of service you shall receive.
Data security should be one of your primary concerns and its best to implement greater security measures than is taken for internal storage. The vendor’s track record will speak for themselves as to how safely they handle data, and getting the vendor to sign a Non-Disclosure Agreement (NDA) prior to receiving company data, is a must. Ensure that the outsourcing contract covers how the vendor needs to store your data, security measures that should be in place, and that they will be held liable if there is data leakage.
Unless it is specified in the contract itself, the service provider is not liable to share with your brand the processes and models of analyzing the data. The vendor implements the analytics model they deem best suited for your industry and your brand, and you simply benefit from access to insightful reporting.
Even though you may not have visibility into the actual analytics processes, your brand needs to be an active participant in collaboration with the service provider. Most of the involvement will be in the discovery stage, when the vendor will need your help to assess the current situation your brand is in, so that they can figure out how analytics can boost your business. Based on this discovery stage, the service-level agreement, or contract, is drafted and signed, prior to the vendor providing the services.
Your brand needs to cover some essential aspects in the contract you offer service providers so that you can retain a modicum of control and the outsourcing is efficient.
Once your analytics roadmap is set up, outsourcing data analytics can enable your business with crucial insights specific to various business functions.
If you are unsure if your brand needs analytics support, the following indicators should help you decide. Consider outsourcing if your brand:
This should make a compelling case for you to consider outsourcing your analytics requirements to a service provider like Course5 Intelligence. Let us take the burden of analytics, while you optimize your business based on the insights gained.
Our AI-based solutions help clients to combat critical problems related to core requirements such as Digital and Ecommerce Analytics, Customer Analytics, Sales and Marketing Insights, and Supply Chain Analytics. Course5 empowers clients at every stage of their business process, from the acquisition of new customers to reducing churn, to improving customer loyalty and driving profitability.
Employing AI and custom Machine Learning models for your analytics outsourcing requirements can enable you to make effective improvements to your brand with respect to the market, your competition, and the customers. Help us to help you leverage your data, make insights actionable and drive digital transformation.
Sign up to get the latest perspectives on analytics, insights, and AI.