How Does an Organization Become Data Smart?

Data Smart Organization
Author Image Gaurav Vohra

More and more organizations are waking up to the power of analytics. They are realizing that analytics is not a niche skill that can be harnessed with a team of 3 or 4 or more data scientists, operating in isolation from the rest of the organization. To leverage the full power of analytics, it has to be embedded within the DNA of the organization. Everyone, from the CEO to the entry level executive, needs to understand and respect the power of analytics. Data driven decision-making has to enter into the core philosophy of the organization and asking for data to validate or back up any hypothesis should become the standard practice.

 

Last year, Jigsaw Academy worked with many organizations to get them started on the journey to becoming “Data Smart”. We worked with one of the largest banks in India to help them achieve this goal. We worked with one of the big names globally in consumer electronics to help them kick-start this initiative in India and Europe simultaneously. We also worked with media companies, consulting companies, PSUs and IT companies to achieve similar goals.

 

As we did this exercise multiple times with multiple companies, we developed our own learning, which helped us refine our approach as we moved ahead.

 

So how does an organization become “Data Smart”?

Any organization that is embarking on this journey to becoming “Data Smart” has to take a three-pronged approach. There are 3 distinct sets of audience that need to be handled differently.

1.     Senior leadership

2.     Rest of the organization that has access to any kind of data

3.     Internal IT/BI/Data Science teams

 

Let us look at the approach to handle each of these audiences.

 

Senior Leadership

 

Senior leadership buy-in critical for this initiative. The leadership team has to be aware of the power of analytics, understand how it can benefit their business and be completely sold on the idea that this is an extremely important evolution for the organization.

 

The senior leadership sessions need to focus on appreciation of analytics and its use within the industry that the organization operates in. The key here is to have a lot of examples and use cases from the same industry. For example, when we conducted this program for the senior leadership of one of India’s largest banks, we added many case studies from the banking sector. We also added examples, national and international, to showcase the latest and the best analytics practices from the industry and educate the leadership team on what their more data savvy competitors are doing.

 

By the end of the session, the leadership team has a good understanding of how analytics is used in their industry, what kind of problems are solved with it, what kind of questions answered and importantly, how their competitors are leveraging data.

 

If the organization already has a data science team, it is a good idea to give some floor time to the internal team as well. Many times, the data science team may already be working on useful data initiatives and this is a good platform to showcase their work and let the leadership team know what is already happening within the company in this space.

 

Senior leadership training is best done through in-person sessions of 4 hours to a day.

 

Anyone in the organization with access to any kind of data

 

The next step in the journey towards becoming “data smart” is an organization wide training on basic skills of data analysis.  The goal of this training is two-fold. The first goal is to make everyone understand and appreciate the power of analytics (similar to what we did for the senior leadership). But this training goes further and actually focuses on techniques for simple data analysis to aid day-to-day decision making. Participants will learn a step-by-step approach to solving any kind of problem with data. They will learn how to use simple statistical measures and tests to make more informed decisions. They will learn how to evaluate choices using data. They will learn how to present their findings in an effective manner.

 

Again, this training has to be customized for the industry of the organization. Examples and case studies need to be industry relevant. It is important to show the participants industry use cases so they can connect better with the problems being solved using data.

 

This training is typically done at a larger scale. The audience is more diverse and maybe scattered geographically. Self-paced is the best mode of learning in this scenario. It does not require everyone to be trained at the same time. Therefore, it allows people to fit the learning into their busy schedule at their convenience.

 

As an example, another of the trainings that we conducted last year was for a large e-commerce company, that had run an extensive exercise of identifying key skills related to data – data management, data analysis and reporting, generating insights and action plans based on insights for almost the entire offshore services organization supporting its business out of India, across multiple functions including supply chain, IT operations, finance operations and others. They created a need matrix of the different skills required for each team and each level within each team, with differing levels of expertise and emphasis depending on role. We were then able to create a very customized learning plan that included a base level training on data management, analysis and insights concepts for everyone, supplemented with additional sophisticated examples and e-commerce case studies as the level of expertise required for some of the senior resources increased.

 

Internal IT/BI/Data Science teams

 

Most organizations have an internal team that is already doing some amount of analytics – whether it’s the BI team or the data science team or even the IT team. Usually this team will have resources that have some amount of knowledge of analytics tools and techniques and need a more advanced program.

 

The curriculum of these advanced programs will depend on the existing skills of the internal team and where they want to get to.

 

As always, the curriculum can be customized to make it more relevant for a particular industry.

 

Such trainings are best done in a hybrid learning mode i.e. a mix of in-person sessions as well as self paced content. Self paced content works well as a pre-read while the in-person sessions can focus on hands on learning. The hybrid mode allows the program to be extended to a longer period of time as opposed to an intensive 5 day all-day training session where learning plateaus after the first couple of days.

 

In our experience, the three-pronged strategy as laid out above works best for most companies with upwards of 500 people. It starts with an appreciation program for senior leadership, then a more hands-on training for a larger audience and finally, specialized curriculum for the existing data science team.

 

However, this by itself is not enough to make an organization “Data Smart”. Becoming data smart is a long journey and this is just the first step. There are a number of follow-ups that we have found to be highly effective.

1.     A more advanced 2nd level program for senior leadership within 6 months of the first program. This is required to re-emphasize whatever was covered in the first session along with additional more updated knowledge.

2.     An analytics newsletter which provides interesting and useful information on analytics to all learners long after the actual training has finished. We believe such a newsletter keeps people interested in analytics and they feel more connected to the field.

3.     More programs like Storytelling with data and data visualization. Once the participants are comfortable with analytics, these additional programs will help them develop other critical skills like the art of storytelling with data.

 

Becoming “Data Smart” is not a one time process. Its an on-going journey. The above programs can set you off on the right path. But how far you go on the path is up to you, your dedication and your perseverance.

 

A great start to building a data smart organization is with Rubric by Jigsaw Academy – a comprehensive, end to end solution to all your training needs.

 


This was originally posted on LinkedIn Pulse, authored by Gaurav Vohra. 

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