Training your workforce for Data-Driven decision-making

Cynthia Trivella
I
4
min read
Training your workforce for Data-Driven decision-making

The power of business driven by data insights is undeniable. But no matter how clear we are about the importance of being able to base key decisions on a clear framework of data analysis, actually applying this approach is another story for many organizations. From leaders to managers to workforces, what’s needed is a program that encompasses all the knowledge, skills and strategies to enable our people to become data-fluent and data-confident, so they can apply data-driven decision-making across the board.

Just why some organizations fall short on this is partially a matter of culture: we may embrace the concept of “data” in our work cultures, yet we fail to commit to developing the analytics skills our teams need to harness the data. It may also be a matter of infrastructure: many organizations simply will not have the means to create, manage, and implement a multidimensional training program on their own. And for some, it is the inability to assess our own limitations: we may not even realize where the gaps are in terms of competencies — or even the technology needed to carry them out. On all these fronts, however, there is no reason to go it alone.

To effectively empower our workforces, it’s a best practice to establish a partnership — one that provides the vision, structure, tools, and collaborative energy to turn our people into data-driven decision makers. If we’re going to transform our work culture to be competitive going forward, that’s what we need to instill data-driven decision- making as a core competency. And we need to be able to capture the imaginations and drive the engagement of a diverse and multi-generational workforce — who may want their learning delivered in a whole range of ways, across different channels, and at different speeds.

Recently I sat down with Donna Trice, Sr. Mgr., Education and Training Division, and Katie Whitley, Education Account Executive, of SAS for a roundtable about just this challenge. We discussed how SAS works with organizations to shape effective, ongoing  partnerships, embarking on a collaborative journey around data literacy and analytics training that carries through from planning to adoption to refinements. It’s a dynamic that thrives when all parties are actively involved. What SAS brings to the table is a level of expertise, perspective and also flexibility that most organizations don’t have, and likely need, to equip and train our workforces to become data-driven decision makers.

Training your workforce for Data-Driven decision-making | peopleHum

What follows are highlights from our conversation:

Assessing Needs

Meghan M. Biro: Something I see in terms of technology now is that it’s not about simply selling and buying. There’s no “one and done” with software and tools that are this powerful and this sophisticated. Learning the technology is also a huge part of being a modern company. True learning partners can’t position something and then walk away. They have to create an ongoing partnership and be responsive to a company’s evolving needs. 

Can you talk about how you assess the individual needs of each company — and what some of the distinguishing factors are? You may be working with a company that wants to be in front of the most cutting-edge skills, and another company that is a bit more traditional. So how do you determine the best route for skills training for each of these workforces? And what are the various methods for coaching and learning that work for one work culture versus another? How do the approaches differ, and what tools do you use, such as learning portals?

Donna Trice, SASWe start by having conversations, qualifying and understanding their learning goals. We work with our clients to look at their skills today and where they want to go. Together, we create a training plan that works for them and their employees.  This may include a learning needs assessment, some may prefer public classes; others may want us onsite; others prefer e-learning. We can bend and flex to cater to customer needs.

It’s all about meeting the customer where they are. So, for companies that aren’t as ready to take a large leap, those that prefer a more traditional approach to learning, they may schedule multiple onsite training sessions up front on multiple topics versus a company that comes to us and says “I want to build out a data science team.”  For that company, we may lay out a six-month plan with different training modalities complete with a custom learning portal and reporting to track progress and outcome metrics. 

Creating the foundation for skills development 

Meghan M. Biro: I’m going somewhat high level here, but do you think part of the gap regarding training and skills has to do with how we envision skills development? We hear a lot about the training that employees themselves need. But it seems like companies also need to take a clear look at the big picture. 

In other words, how can we better equip our leaders and managers and learning teams to make the right decisions for their workforce, and develop that 20/20 vision? What’s the right approach for working with leaders to develop a real base of knowledge — so they can set a course for learning and development that fully utilizes the capabilities of their own technologies?

Katie Whitley, SAS: This is such an interesting question — and there are many sides to the answer. We need to look at skills development with our customers two ways: macro and micro. And we need to give customers the confidence that we can help tackle both.

The macro is important so organizations can see the big picture of skills development — how it will affect and benefit the entire workforce. It’s not just getting their people trained. It’s understanding their jobs, the skill set needed to be successful and exceed beyond that, and their current ability to meet those expectations. In other words, where are they now and where do they need to be to meet their business objectives? It’s also important to understand how making these advances forward will not only benefit one group but create efficiencies company-wide.

But not everyone will need the same plan to succeed. Once you have the big picture of how skills development will benefit your organization at the macro level, you need to look at the individuals and get a true understanding of the current skill levels and not only understand their gaps, but their ability to learn, and the format in which they learn best. Creating role-based plans specific to an individual’s learning needs will ensure the employees are getting a tailored, prescriptive plan — where success can be tracked and measured.  

And, the most critical piece to success is ensuring knowledge and skills are building up. Because, let’s face it, there are lots of e-learning platforms out there. SAS pays critical attention to this part, and issues completion badges and globally recognized certifications to validate skills gain. We’ll even step in with mentoring and coaching if it’s needed to advance knowledge gain. 

Mentoring hours and certifications are a great way to achieve this. When you combine this with role-based plans that look different for a business analyst versus a data scientist, administrator or model manager, that’s where you get success. As a business, you have to prioritize these plans according to your goals and find the right learning partner to get you there.

The Future of Work

Meghan M. Biro: Looking forward, we want to make sure our workforce masters in-demand software and tools. I know certain careers are starting to really pick up, like data science, where jobs are growing by 29% this year. Given the job starts at around six figures, I’m not surprised it was LinkedIn’s most promising job for 2019. But skills in data science require a lot of very specific learning — and we see a lot of gaps in our current workforce. 

What will it take to better train our workforce — and ensure the next generation is ready to work with AI and machine learning? I’m also thinking of education: How does learning cross over from the workforce into the academic arena?  

Donna Trice, SAS: SAS’ approach to building the next generation of data scientists, programmers, and AI and machine learning experts is rooted in building collaborative relationships between businesses and academic institutions to ensure there is an analytics talent pipeline that businesses so desperately need. 

This can take the form of free training and enablement, such as course materials and workshops, to help faculty build their curriculum, along with low and no cost SAS software options. We also work with academic researchers, providing them with access to powerful SAS Analytics so they can extract deeper meaning and insights from large amounts of disparate data.

All of that said, in order to truly fill the analytics skills gap, there has to be a partnership between analytics companies like SAS, universities, and industry. SAS is finding creative ways to be there to support universities who want to give their students a competitive edge in the labor market, while also helping commercial customers find and hire the early-career talent they need. The key is building collaborative relationships between SAS’ industry and academic partners — to ensure alignment between the analytics skills that faculty teach, and that students learn, and what industry needs to grow and succeed.

We hope you got some great insights from this blog. Its now time to apply it. Get started with peopleHum for free today. No credit card needed.

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data
decision making
workforce behaviour
workforce technology
employee development
employee management
peoplecentric
skills
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futureofwork
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