Post on 22-May-2020
To what degree is the collection of Big Data and processing of Advanced Analytics
automated at your organization?
9%
15%
37%
25%
15%
A great deal A lot A moderate amount A little None at all0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
9%
15%
37%
25%
15%
A greatdeal
A lot
A moderateamount
A little
None at all
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
CURRENT STATE: BIG DATA & ADVANCED ANALYTICS IN SUPPLY CHAINAPQC and Supply Chain Management Review collected information in April 2019 from supply chain professionals about the use of Big Data & Advanced Analytics in supply chains around the world.
Big Data is structured and unstructured data sets that are too large or complex to be dealt with by traditional data-processing application software. Advanced Analytics is a technology enabled, complex process 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.
WORK SMARTER, NOT HARDER
There is still ample room for advancement in automating the collection of big data and processing advanced analytics. Only 9 percent of participants report a great deal of automation for these processes in their organization.
Automating big data and advanced analytics gets intelligence to decision makers significantly faster, allowing for more agile and informed decisions. The goal is to ensure that leadership has the insights and tools to make evidence-based decisions.
The good news is that investment is on the rise. Over the last three years, 69 percent of respondents have seen their organization’s investment in advanced analytics increase.
EFFECTIVENESS OF ADVANCED ANALYTICS
BENEFITS OF BIG DATA & ADVANCED ANALYTICS
Does your organization want better forecast accuracy and visual tools? Invest in advanced analytics: 2/3 of respondents report these as realized benefits.
HURDLESTO WIDESPREAD USE OF
BIG DATA & ADVANCED ANALYTICS
The biggest barrier to advanced analytics is a lack of people with the needed skills. While the main requirement is analytical skills, these pivotal employees also need a good understanding of the business to provide solid advice.
www.apqc.org
Date Collected: April 2019. Number of respondents = 81
As an emerging practice, advanced analytics is very or extremely e�ective in only about 1/3 of respondents. For this percentage to increase, the output needs to be fast, accurate, and easy for leaders to understand.
of respondents have invested in an internal, centralized team to make this happen. And only 2 percent have turned this over completely to an external firm.
Over the last three years, how has your organization’s investment in Advanced Analytics
changed?
28%
41%
28%
1%
1%
Increasedsignificantly
Increased slightly
Stayed the same
Decreased slightly
Decreasedsignificantly
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
28%
41%
28%
1% 1%
Increased significantly Increased slightly Stayed the same Decreased slightly Decreased significantly0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Increased significantly Increased slightly Stayed the same Decreased slightly Decreased significantly
28%Increased significantly
41%Increased slightly
28%Stayed the same
Over the last three years, how has your organization’s investment in Advanced Analytics
changed?
28%
41%
28%
1%
1%
Increasedsignificantly
Increased slightly
Stayed the same
Decreased slightly
Decreasedsignificantly
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
28%
41%
28%
1% 1%
Increased significantly Increased slightly Stayed the same Decreased slightly Decreased significantly0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Increased significantly Increased slightly Stayed the same Decreased slightly Decreased significantly
28%Increased significantly
41%Increased slightly
28%Stayed the same
Over the last three years, how has your organization’s investment in Advanced Analytics
changed?
28%
41%
28%
1%
1%
Increasedsignificantly
Increased slightly
Stayed the same
Decreased slightly
Decreasedsignificantly
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
28%
41%
28%
1% 1%
Increased significantly Increased slightly Stayed the same Decreased slightly Decreased significantly0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Increased significantly Increased slightly Stayed the same Decreased slightly Decreased significantly
28%Increased significantly
41%Increased slightly
28%Stayed the same28% 28%41%
How would you rate the effectiveness of Advanced Analytics at your organization?
7%
25%
31%
25%
12%
Extremely effective
Very effective
Moderately effective
Slightly effective
Not effective at all
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
7%
25%
31%
25%
12%
Extremely effective Very effective Moderately effective Slightly effective Not effective at all0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Which of the following, if any, do you see as benefits of Big Data and Advanced Analytics
in your supply chain? (Please select all that apply.)
65% 65%
56% 56%
49%
Improves forecastaccuracy
Provides visualtools such asdashboards
The ability toanalyze unstructured
data
Provides the abilityto model
hypotheticalscenarios
Reduces analysis andforecasting cycle
time
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
65%
65%
56%
56%
49%
Improvesforecastaccuracy
Providesvisual
tools suchas
dashboards
The abilityto analyze
unstructured data
Providesthe abilityto model
hypothetical scenarios
Reducesanalysis
andforecastingcycle time
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
# Field Percentage
1 Improves forecast accuracy 18%
2 Reduces analysis and forecasting cycle time 14%
Which of the following, if any, do you see as hurdles to the widespread use of Big Data
and Advanced Analytics in your supply chain in the next 2 years. (Please select all that
apply)
65%
55%
44%
33%
23%
Lack of people withthe necessary skills
use the technology
esistance to change
Lack of access todata across disparate
systems
Financial constraints
Lack of compellingbusiness case
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
65%
55%
44%
33%
23%
Lack of people with the necessaryskills to use the technology
Resistance to change Lack of access to data acrossdisparate systems
Financial constraints Lack of compelling business case0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Q6_7_TEXT - Other (please specify)