Analytics has been around ever since the human race learned calculations, but it has picked up steam in the last few years owing to the hype and powerful marketing done by major internet firms.
The term analytics refers to the ability to analyze something and derive meaningful insights from it. The insights need not be limited to the count or to a particular field. The insights can vary in size, number, or in their relevance for the audience. In fact, if done beautifully, the insights can even lead to another discovery or an opportunity for further analytics.
For example, the most recent escalation of one of the social media giants with regard to leaking users’ data to one of the analytics firms in Cambridge highlighted this field much more albeit through negative publicity.
It seems that the firm was using this data and its analytics capability to help its customers fine-tune their marketing and advertising campaigns for political benefits. The ethical and lawful discussions on this matter will take a long time to settle down.
But this episode does show us that analytics is a capability that has immense power to decide our future course of action, and it should be used diligently and wisely.
This is where Project Management becomes an important key skill for Analytics. That also explains why the new-age IT professionals are taking up project management courses like PMP courses to validate their skill sets.
Why Project Management?
Project management is a field dedicated to managing all the aspects of a project, program, or key initiatives. If we consider Analytics as one of the projects within a company where let’s say, we have been assigned a team.
Now, as a project manager, you will be required to manage the team dynamics and team communications, set the team goals, understand the goals of business owners, govern ethics and rules of the game, punish the culprits and reward the good players of the game.
And the bottom line will rest with the Project manager like it did with Mr. Zuckerberg.
How to Use Project Management Skills in the Analytics Field?
If you have been assigned as a project manager for the analytics project, immediately, your goal should be multi-fold.
1. Constitute the team in next few days
Any more delay in this matter will make it difficult for you to develop and deliver high-quality insights in time. Because as clichéd as it might sound, developing key insights by looking into data is no child’s play.
2. Assign the following roles within the team
Your team should have the following members, and their responsibilities should be clear to them. Data gatherer: This person will be required to gather the data relevant to your project from all the required sources.
Data validator: This person is responsible for making sure the data collected is in a good state to be consumed and is not incorrect. For this, the person will need to use various data validation programs and methodologies before he/she confirms the data is consumable.
Data organizer: Once you have the data collected, reviewed, validated, and ready to be consumed, you need to organize it. Either in the form of database tables or queues or in plain simple excel, but you need it organized. And not only in 1 view or format but in multiple formats. But the key ingredient of delivering insight comes from the ability to view the data from multiple angles and views; which views and angles will suit your needs best is decided by none other than a data scientist.
Data scientist: The person everyone looks up to and who gets the maximum respect in the Analytics project is a data scientist. This person supposedly knows all the algorithms, data-crunching models, views, and possible depictions of data. The Data scientist will guide your data organizers and programmers on the actual technical on-the-ground needs of the project.
Programmers: Sharp technical people who know how to code and do it fast. Time is money when it comes to analytics.
And some key people with good skills in talking to the data: None other than the project manager himself is best suited to play this role, as long as he/she is comfortable working with data. I think this is given by default that any good project manager worth his/her salt can play with data and talk to it. Still, some people have an uncanny knack for going one step beyond and having the data talk to them. This is where no mathematical model or algorithm will help you. This knowledge and insight come from observation, communication, and being aware of the circumstances driving the project. And who else has these things better under their control than the project managers themselves?
Meet with key business owners of the project and understand their goals
Explain, iterate and re-iterate those goals with your teams, especially data organizers, data scientist,s and programmers
Start planning insight development and views on a unified dashboard for everyone to see.
These are the top 5 work items that any project manager should do in order to have a working analytics project.
3. Tying the loop
Needless to say, ensuring the team respects the rules of the team, the correct hierarchical order is set, and, most important, ethics are maintained whereby no consumer data is compromised, leaked, or misused is again one of the most important responsibilities of a project manager. If the project manager is juggling multiple responsibilities in the team, then the above can be delegated to additional members known as team moderators.
What a Project Manager Possesses that a Data Scientist can Never have?
Data scientists are a respected lot. They command respect and authority wherever they go because they have the tools and techniques to bring out the best of data hidden under the layers of algorithms. But still, there is something a project manager can make or break the insights that are going to come out of Data. An extra something is Intuition. This intuition is what tells a project manager whether he should stop now or should the team dig deeper to gain more insights. This intuition is what tells the manager that a particular dead end in analytics [and you will encounter many in the journey] could be another opportunity for a breakthrough.
The project gains this intuition in the following manner:
Through experience. Nothing can beat experience. The experience of dealing with data is very critical here.
Through observations. Observing the surroundings. Observing how data and systems interact with each other under different circumstances goes a long way in developing the art of understanding data.
And finally, through communication. In this case, communication with the business owners. For example, your team might be delivering a lot of insights by reading the data. And they could be right. But if this is what your business owners want, then what use will those insights be off? So communicating frequently and keeping everyone on the same page is very important here.
Gaining insights from data through Analytics is not only a science but an art. It is a beautiful symphony that, when played right, makes the data start unfolding itself in front of you without much effort, leaving you with treasures to be enjoyed and delivered.
Abhinav Gupta
Blog Author
PMP, has 12+ years of experience working in Information technology sector and has worked with companies like Infosys and Microsoft in various capacities. He started his career as a manual tester for a world renowned software product and grew on to become automation champion in both functional as well as UI. He has worked with Healthcare units providing various software solutions to companies in North America and has worked with search engine based groups to enhance their experience and provide more bang for buck to their customers.
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