Building a Team vs. Contracting a Team
There are two major methods for attaining the power of analytics and the insights it can provide for a business: hiring an outside analytics team or creating your own in-house. This article will walk through the methods and benefits of building your own analytics team as well as the reasons and benefits for working with an outside analytics team.
Building an in-house team
With analytics providing massive benefits across businesses, forming internalized analytics teams has been the solution for many companies to obtain the insights stored within data. The design and impact of internalized teams is dependent on three important factors: business needs, available resources, and business structure.
Business Needs
The primary step for building an in-house analytics team is to determine the organizational benefits you are hoping to obtain through analytics. Are you trying to improve reporting? Build machine learning applications to predict or monitor some metric? Or are you just trying to better understand operational efficiencies in your business by improving data management and tracking? There is a large diversity of benefits an internal analytics team can provide but identifying your key businesses needs and highest ROI analytics projects will enable you to use your team efficiently. The role of analytics can be more focused towards making continuous improvement (like marketing plans, finance, logistics, etc.) or it may be more focused on innovation. Determining the best course of action for your business will enable the selection of proper personnel and team structure.
Available Resources
The next important step an organization must conquer when designing their own analytics team is determining the number of resources that they can allocate towards it. What is the budget around hiring diverse personal capable of performing the required organizational benefits they are looking for? In the beginning of an internalized analytics team only one or two analysts are normally hired to try and implement the desired analytics projects. But depending on your organizations desires, larger amounts of diverse analysts with various expertise’s are needed. The ability to fill your team with needed experts to achieve your analytics goals is limited to budget capacities and may not be possible in present circumstances.
Business Structure and Context
Business structure and organizational context also plays into the construction of an internalized analytics team. Depending on the role of the analytics team, there might be limitations on how they can operate in various facets of the business. This is where various types of internalized models should be considered:
Centralized Analytics Teams – Have a single core of analysts and data scientists that act as the driver for how analytics is used throughout the origination. They take projects from all departments and act similar to an internalized consulting team
Decentralized Analytics Teams – Each department has their own analysts and only tackle problems within their departments.
Mixed Teams – Both centralized and decentralized with a centralized team reporting to a chief data scientist but resources are loaned out to departments to tackle department specific problems.
Again, the type of team that is most suitable for your organization is dependent on the decision making benefits you are expecting from analytics, your available resources, and how ingrained you want analytics to be within all employees across all departments.
There are plenty of resources available when deciding on the best approach for building your own analytics teams. One mentioned by Keith McNulty, an analytics leader at McKinsey depicts a 6 step process of implementation as seen below. However, there are plenty more resources available on how to go about designing and implementing an analytics team and can be found here, here, and here.
https://towardsdatascience.com/how-to-build-an-analytics-team-for-impact-in-an-organization-21bb05925587Working With an Outside Team
Working with an outside analytics team provides a lot of the benefits of an internalized team but often with fewer overhead costs and internal organizational changes. The steps for producing impactful analytics are generally the same, from deciding the appropriate context and organizational improvements desired from analytics, to understanding resource capacities and subsequently building the appropriate solution. However, with an outside team the expertise and diverse range of knowledge around business use cases is already installed without the need for hiring a large and diverse number of employees like in the internalized case.
Because data science and analytics is a broad discipline generally requiring multiple skill sets, working with an outside analytics team gives you access to this wide range of available expertise. For example, imagine for the price of hiring one internal analyst capable of doing data management and dashboarding, you are able to gain access to a developer, a data analysts and a machine learning expert. Instead of having 100% of the time with an internalized data analyst, you are able to achieve access to 33% of a developers time, 33% of an analysts time and 33% of a machine learning experts time all at close to the same cost!
In addition to the wide range of expertise that becomes available for cheaper with external analytics teams, the wide range of experiences and use cases that these experts have experienced also become available. Enabling the business to gain access to their frameworks and ideas towards solving similar problems that your organization may be facing.
Working with outside teams is beneficial not only for generating a solution to your current problem, but also for creating an analytics oriented mindset within an organization. While working alongside experts they will be able to guide you in the right direction to incorporating your own analytics teams as well. Coaching on what might be useful in your organization to expand on the work that has been done during the engagement. This method for incorporating analytics is extremely useful for smaller companies or companies with little resources to assigned to the formation of analytics teams. It can also enable larger companies with beginner analytics teams to evolve into a more influential analytics oriented business.
Conclusion
Whether it be building your own analytics team or working alongside an experienced group of analytics professionals, data and analytics contains to power to transform any business. Both options provide relatively easy gateways for any business to begin or enhance their analytics journey.