An Analytics team can be the defining factor of your business model. It’s vital to ensure that the Analytics team is doing their job correctly to ensure the success or closure of a business.
Before going further to the topic, what exactly is an Analytics team in a business, and why do we need it so badly?
Well, an analytics team is a group of people dedicated to gathering all the big data of a particular company. They then take the help of this data to design future business models and strategies. From IT to Marketing, an analytics team will tell how the policies should ensure the best productivity and brand value. FoxMetrics is an example of an analytics team.
The main issue persists when there is no discipline in the Analytics team. Most often, we assign people from irrelevant departments to collect and administer the data. Inexperienced people can bring no use to such a massive pool of data. Therefore, experts in Analytics must be employed for this matter.
Hence, if one wants to update their business and marketing policies, they must hire a new Analytics team. The team can consist of 5 or more members. It’s better to assign roles and a list of responsibilities to each member of the team. If you think that one of the team members is overloaded with tasks or doesn’t have much work, it’s better to share some responsibilities.
If you cannot afford more employees, you can hire one person with two analytics skill sets. This will save cost but increase workload and time.
As a manager/owner, you have to check if the hired people are capable enough. Sometimes a qualified team member cannot perform well in their assigned role, but they can fit some other part, so it’d be better to transfer them.
Also, try to add those people in the Analytics team that can fulfill other people’s role in case of any emergency. Remember that the final authority and responsibility is still yours.
Based on the facts said above, let’s break an Analytics team into roles. Ideally, five prominent roles are enough to run the team. One can add supporting roles too. The five leading roles are:
- The Project Head
- The Data Analyst
- The Business Analyst
- The Product Developer
- The Reporting Developer
Let’s dive further and explore what these roles are responsible for and how you can assign them to the right people.
The Project Lead or Manager has the most significant responsibility of the analytical team as he is responsible for initial reports and their solution and implementation. An Analytics project has many responsibilities.
First of all, he has to set specific guidelines along with a period. This goal setting will broaden up the scope. Also, make sure that every Analytics team member is equally involved.
Furthermore, the Project lead has to figure out what’s at stake. They need to know the basic structure of the business and plan the Analysis accordingly. They also need to ensure that their assigned project makes it till the end and all team members fulfill their responsibilities. Remember, data collection is vital.
The manager also has to eliminate all hurdles that can get in the way of mining data and its execution. They also need to assign roles to the team and make sure that they fully understand and acknowledge their responsibilities to the project lead.
As a good manager, it’s for you to decide whom to bestow what role. It’s better to ask the team members too about their expertise before assigning roles.
In the end, the project Lead will be responsible for all the members and their performances. It’s for the lead to do periodic surveillance and push other members to adhere to project deadlines.
A data analyst is one of the most crucial jobs inside the Analytics team model. The responsibility to understand and create a data model is on the shoulders of a data analyst.
The data analyst has to identify the complexity of a particular data model. They can modify the model and add some critical actions to it. They are given the liberty to include whatever properties they deem necessary.
The data model made by the data analyst defines the magnitude and future scope of the project. They also demonstrate what business queries are possible to answer and what is not.
The data analyst can also take help from previous data models or reviews. This will not only save time but put more research into the project too. They need to model their data in a language that is familiar to other users.
The best tip for data analysts is not to over-complicate their models. Simplicity and following professional tricks and tips would do the job instead.
The Business Analyst is the one who collects heaps of useful data. Developers of the team then use the data to convert it into useful information to help a particular business.
The business analyst will analyze each scenario and question the authorities and present their share of ideas to the team. In this way, a new Analysis takes place to better the business model.
The Analysts are also responsible for providing the solution plan. If we take a detailed look at the team, then the Business Analysts collect raw usage data and transfer that data to the Data Analyst/Architects to execute this data.
A good business analyst is one who maintains proper communication with other team members. They sometimes face situations where they have to explain their findings, so they have to prepare for everything. Employees with a technical background can become good business analysts.
Product Developers play huge roles inside an Analytics team since the beginning. They have to perform necessary coding so that they can collect the data from the purchase, uploading, and other actions happening inside whenever someone logs into.
A Product Developer is most likely able to perform the duties of a data analyst too. Consistency is, however, required for a Product developer.
The PDs are also responsible for setting up the tracking for analytics, and it’s best if the set-up remains simple and straightforward. They can again ask other team members for tracking options. It’s highly crucial that the implemented tracking makes sense to the manager and other team members.
Once the tracking is deployed, it’s best if the PD asks someone from a similar experience to review the data to omit any errors in the model. There would be some minor or major mistakes that sometimes a PD cannot detect, so having someone with a second opinion can surely help.
Lastly, one of the main backbones of an efficient Analytics team is a reporting developer. The irony is that many people ignore the role but building a documented report on the entire work can help your company and the future employees and policies.
Incorporating data into the business workflows can be more beneficial than abandoning it in a database where one must log in to retrieve the data. A reporting developer can transform the queries into informational reports that the Product Managers and others can access.
Moreover, the Reporting developers can also report web analytics and mobile analytics better. Their reports can be in the form of weekly summary emails, on the business webpage, on the dashboard, Google sheets, or if pushed to slack channels and salesforce, or inside customer-facing applications.
The Reporting Developer also has to ensure that the codes are put in their necessary places and that the production data and testing samples are arranged accordingly.
A good tip for the reporting developers is that they should be much descriptive while forming their reports. They can insert footnotes that will further explain how they collected the data and from which source, and how they analyzed the collected data.
Now, most people will inquire that these jobs are not a great deal and only one or two people can do the Analytics work. Well, it all comes back to the capabilities of an individual. Being a good report writer doesn’t imply that he can perform coding too.
Moreover, analytics is as crucial as the business itself. The change in time leads to changes in the data and metrics, so a fully functional Analytical team is highly needed.
Hence, it is concluded that at least five members must be on an Analytics team as they can combine their brains for the company’s goodwill. It’s highly crucial for all analytics members to be on the same page and communicate as much as possible.