The recent uptick in the usage of big data in business and subsequent demand for data analytics is evident across several industries including industrial and manufacturing.
Data analytics and leveraging findings from it to inform operational decisions have helped companies like FedEx and Walmart gain a competitive advantage over those that aren't as strong in this area. Given this success, IDC says the worldwide market for big data and business analytics will show an annual compounded growth rate (CAGR) of 11.7% from 2016 to 2020.
What is data analytics?
Data analytics is the pursuit of extracting meaning from raw data using specialized computer systems. These systems transform, organize, and model the data to draw conclusions and identify patterns.
Simply put, data analytics lets us compile information from various software like Customer Relationship Management (CRM) or Enterprise Resource Planning (ERP) systems and analyze the data to make informed business decisions related to supply chain planning, inventory management, new product lifecycle management, asset management and more.
There are many benefits of establishing a data analytics mindset for an industrial or manufacturing company including the following:
- Improve supply chain and inventory management efficiencies
- Gain competitive advantage in the marketplace
- Increase revenues while lower costs
- Make informed organizational and operational decisions
- Benefits of outsourcing data analytics
Having an in-house analytics team seems like a no-brainer. In a perfect world, yes. If investing in an in-house data analytics team isn't currently feasible, consider outsourcing those skills and services to reap the same rewards.
Critical insights with lower cost and risk associated
Outsourcing data analytics activities doesn't mean you have to sacrifice value or quality as long as you choose to work with a trusted, experience partner.
The reality is that this skillset is in high demand and the current talent pool can’t accommodate that demand. A 2011 report from McKinsey Global Institute says by 2018, the United States alone could face a shortage of 140,000 to 190,000 people with deep analytical skills as well as 1.5 million managers and analysts with the know-how to use the analysis of big data to make effective decisions.
If you can still have the critical insights associated with the analysis of data without taking on the associated risk and large investment of building out a complete in-house team, why wouldn't you?
Not only can you minimize risk and decrease costs, you can be improving efficiency related to supply chain and inventory management. In the long run - and if done properly - this can lead to lower costs and increase revenue.
Show executive leadership benefits without full investment
Building a comprehensive, highly-skilled in-house analytics team is a hefty undertaking - in time and money. Getting executive leadership on board can require a strategic roadmap on its own.
Oftentimes gaining leadership buy-in can be a catch-22. They’ll want unwavering confidence in your plan to commit to it along with strong evidence of the return on investment (ROI). You can compile research and reports on success stories and connect your plan back to the business goals, but it might not be enough.
Outsourcing is a great middle ground in which you aren't asking for the full investment of time and resources, but you’re still expecting positive results for operational efficiencies, reduced costs and increase revenue. Something we can all feel confident about leadership being thrilled with.
Expand internal data analytics capabilities
There are several different ways you can structure a partnership when outsourcing data analytics. For example, if you have in-house analysts they can be focused on developing new, innovative capabilities to gain a competitive advantage in the marketplace while outsourced resources can tackle less strategic (yet still critical) activities like compiling reporting metrics to inform strategic initiatives.
This way, you essentially get the best of both worlds and you don’t necessarily have to give up one for the other. Both team can be working in tandem on parallel tracks to gain momentum and move the needle.
Outsourcing data analytics: A win-win
When you step back and look at each factor involved in having an in-house data analytics team versus outsourcing to a trusted partner, it’s clear that outsourcing these critical business activities can hugely benefit industrial and manufacturing companies. Outsourcing can provide companies with the insights necessary to make informed decisions that can improve efficiencies, freeing up time to be a strategic player in the increasingly competitive marketplace.