Is This the Supply Chain Apocalypse? You’ve Got 2 Options to Save Your World

Regardless of your industry or sector, new technologies and advanced analytics are whipping through supply chain departments like wildfire.  It’s no longer enough to be Excel-savvy or have the latest instance of Oracle.  Today’s Supply Chain department needs data scientists and highly competent analysts to turn all that noisy data into information your planners and buyers can execute on. The magic in transforming that data?  Machine learning and Artificial Intelligence tools.  

But the talent to make the tools sing? Good Data Scientists, who are hard to find, and expensive.   

Take a hard look at your team’s data analytics capabilities.  According to a 2015 Deloitte report, only 38 percent of all executives surveyed say they are extremely or very confident that their supply chain organization has the competencies it needs today.  The report also stated that more than 95% of the supply chain leaders identified advanced analytics, including optimization and predictive analytics, as the foremost capability of the future.   

So, here are the questions you should be asking yourself –  

  • Does your team have the technical expertise to run the supply chain required by today’s market speed?   
  • Do your supply chain analytics consist of folks “running queries” out of your systems?  Creating pivot tables?  Maybe a filter or two?    

Competitive supply chains have moved past that “basic” level.  The future is clearly in machine learning platforms, customized algorithms and AI tools to speed up predictive analytics and modeling capabilities.  Lagging behind in advanced reporting capabilities and accuracy will soon equate to a very serious competitive disadvantage.  Poor analytics can have a catastrophic impact in bringing new products to market, potential inventory carrying costs, etc.  If your team doesn’t have the analytic skill sets you need today, how are you formulating the remedy for tomorrow? 

It’s time to play supply chain’s favorite game:  Make vs. Buy. 

As I see it, you’ve got two options.  Hire and grow the talent internally OR find yourself a partner.  Let’s explore the pros and cons of each option. 

 

Option 1:  Make.   

Hire and grow your talent and make retention of that talent a top priority.  

Pros: 

  • The upside of this strategy could be phenomenal with the potential to make a hire that could have a singular focus and create data solutions to revolutionize your process and production.  

Cons: 

  • According to IBM, by 2020, data scientist/ analyst job openings are projected to grow by 28%. With that rise in demand comes a rise in salaries to six figures. Your analysts could quickly become your largest FTE cost. 
  • Also with the rise in demand comes and intense competition to retain the talent you’ve invested in.  Every day LinkedIn is sending your analyst sexier and higher paying opportunities.  McKinsey’s 2016 Global Institute Report notes approximately half of executives across geographies and industries reported greater difficulty recruiting analytical talent than any other kind of talent. 40% say retention is also an issue.  

 

If option 1 isn’t a budget or HR gamble you are willing to take, we can move to option 2.  

 

Option 2: Buy. 

Find yourself a trusted partner and transfer the risk of hiring, training and retaining.  Traditionally, we look to consulting firms to augment our internal teams with their expertise, industry best practices and superior analytics skills.   

Pros: 

  • Supply chain analytics as a service has become a hot offering and you have more options available now than ever before. 
  • The risk of hiring, training and retaining is transferred to your partner. 
  • Internal bias and politics are removed as a variable in your analysis results. 
  • A “buy” solution should provide you greater ROI, data accuracy and actionable results at a lower cost than you could hire.  Be sure and kick the tires and lift the hood to ensure you are choosing a partner that aligns with your needs and interests. 

Cons: 

  • True, you won’t have your best forecasting team “in-house” but you also won’t have the costs or performance anxiety to deal with either. 

 

Keep in Mind: 

  • It’s imperative to choose a partner that knows your business, customizes their offerings to your needs and guarantees an ROI or KPI’s.   
  • With these arrangements, the devil is in the details.  Do you have a consistent team running your data?  Are their analysts offshore or local?  Do they have supply chain expertise in your industry and/ or segment?   

While it may be the end of the world as we know it, we are not facing a supply chain analytics apocalypse.  With a strategic approach to growing your supply chain technical skill set, either via growing your own talent or hiring a supply chain analytics partner, you can be well positioned to thrive in the age of advanced analytics.

 

Contact Kristi

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