Nearly 65% of organizations in APQC's 2024 Supply Chain Priorities and Challenges research picked big data and advanced analytics as the top trend expected to most significantly have a major impact on supply chains in the next three years.
Big Data involves structured and unstructured data sets that are too large or complex to be dealt with by traditional data-processing application software.
Advanced Analytics refers to technology-enabled, complex processes of examining large and varied data sets to uncover information including hidden patterns, unknown correlations, market trends and customer preferences that can help organizations make informed business decisions.
Organizational Structure for Advanced Analytics
There are often questions about whether organizations are adopting a centralized or decentralized approach for conducting supply chain analytics. The most common approach (33% of respondents) for conducting advanced analytics is using an internal centralized team (Figure 1). Some benefits of centralization include more efficient decision making, faster implementation of decisions, and reduced costs. Another quarter of organizations have adopted a hybrid model for advanced analytics with an internal centralized core team coupled with decentralized staff in business units. This approach allows them to gain many of the benefits of centralization while also getting direct input from staff members that are at the local level and, therefore, closer to the customer.
APQC Fig. 1
Additionally, 25% of organizations report using a combination of internal and external resources for advanced analytics in supply chain. Bringing in outside resources as needed allows these organizations to tap into a broader pool of expertise and supplement with specialized knowledge while adding flexibility with less fixed cost. However, only seven percent fully outsource these activities to an external firm.
Evaluating the Effectiveness of Advanced Analytics
Over the last three years (from 2021 to 2024), an overwhelming majority of organizations (87%) have seen their organizations increase their financial investments in advanced analytics. This level of funding increase naturally leads to the question of return on investment and whether this investment has been effective. APQC's research finds positive news: the use of advanced analytics in supply chain is highly valuable to many organizations. A significant percentage of respondents (72%) have found advanced analytics to be very or extremely effective in producing supply chain insights for their organizations.
Benefits and Obstacles to Leveraging Advanced Analytics in Supply Chain
In addition to generally finding advanced analytics to be effective, supply chain organizations have found a number of specific benefits of adoption, with higher employee productivity and greater forecast accuracy at the top. The top five benefits reported are:
- Improves employee productivity
- Improves forecast accuracy
- Enables analysis of unstructured data
- Reduces analysis and forecasting cycle time
- Provides the ability to model hypothetical scenarios
If organizations find advanced analytics to be effective and the practice yields many useful benefits, what are the obstacles to widespread use? The top obstacle to higher rates of adoption cited by 52% of organizations is the lack of people with the necessary skills to use the technology.
APQC Fig. 2
This skills gap should be an urgent call to action for business leaders to invest in recruiting as well as upskilling and reskilling critical internal employees. Given that big data and advanced analytics is predicted to have a significant, major impact on supply chains in the near future (and the impact is already becoming visible today) coupled with the increasing levels of funding for it, the clear benefits reported, and the fact that only seven percent of organizations fully outsource it, there is no excuse to not focus on investing in employee learning and development to fully leverage and derive the maximum benefits from advanced analytics.
Figure 3 shows the top five obstacles to widespread use of advanced analytics.
APQC Fig. 3
As supply chains face ever-increasing amounts of data from internal and external sources, many organizations are finding value in embracing advanced analytics to handle the big data they are facing. Investment is increasing and benefits are clear, but more than half of organizations are facing skills shortages that prevent them from maximizing the value of this critical activity. Supply chain leaders seeking a competitive edge must prioritize hiring and training and upskilling employees to be fluent in the skills needed to thrive. Building and coaching a team that is prepared to focus on big data and advanced analytics can offer an advantage as firms seek to compete on an ever-shifting supply chain playing field.
