ENDE

The S&P 500 D.O.P.E list

The biggest winners of Decision Optimization

Still wondering what your company or your competitors lose by making management decisions the outdated way? Explore how much companies are about to gain by optimizing their management decisions every single year with our Decision Optimization Potential Estimates (D.O.P.E) for the 500 largest US stocks.

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10
out of
100
items
Company
losses*
opportunity**
Heading
Employee category
10001+
Market cap
Large-cap
Revenue category
$1B to $10B
Sector
Technology
FTE days lost*
213398
days per year
Productivity losses*
104
$  M
Value at risk*
788
$  M
Avg. failure risk*
58
%
FTEs unblocked**
78957
days  per year
Producitivity gains**
38
$  M
Risk reduction**
284
$  M
Avg. risk reduction**
36
%
Heading
Heading
Employee category
1001-5000
Market cap
Large-cap
Revenue category
$1B to $10B
Sector
Real Estate
FTE days lost*
15579
days per year
Productivity losses*
8
$  M
Value at risk*
879
$  M
Avg. failure risk*
58
%
FTEs unblocked**
5764
days  per year
Producitivity gains**
3
$  M
Risk reduction**
316
$  M
Avg. risk reduction**
36
%
Heading
Heading
Employee category
10001+
Market cap
Large-cap
Revenue category
$1B to $10B
Sector
Healthcare
FTE days lost*
114441
days per year
Productivity losses*
56
$  M
Value at risk*
826
$  M
Avg. failure risk*
58
%
FTEs unblocked**
42343
days  per year
Producitivity gains**
21
$  M
Risk reduction**
297
$  M
Avg. risk reduction**
36
%
Heading
Heading
Employee category
5001-10000
Market cap
Large-cap
Revenue category
$1B to $10B
Sector
Financial Services
FTE days lost*
87814
days per year
Productivity losses*
43
$  M
Value at risk*
838
$  M
Avg. failure risk*
58
%
FTEs unblocked**
32491
days  per year
Producitivity gains**
16
$  M
Risk reduction**
302
$  M
Avg. risk reduction**
36
%
Heading
Heading
Employee category
10001+
Market cap
Large-cap
Revenue category
$10B+
Sector
Consumer Defensive
FTE days lost*
264387
days per year
Productivity losses*
129
$  M
Value at risk*
749
$  M
Avg. failure risk*
58
%
FTEs unblocked**
97823
days  per year
Producitivity gains**
48
$  M
Risk reduction**
270
$  M
Avg. risk reduction**
36
%
Heading
Heading
Employee category
10001+
Market cap
Large-cap
Revenue category
$10B+
Sector
Consumer Cyclical
FTE days lost*
491004
days per year
Productivity losses*
239
$  M
Value at risk*
635
$  M
Avg. failure risk*
58
%
FTEs unblocked**
181671
days  per year
Producitivity gains**
88
$  M
Risk reduction**
229
$  M
Avg. risk reduction**
36
%
Heading
Heading
Employee category
10001+
Market cap
Large-cap
Revenue category
$10B+
Sector
Healthcare
FTE days lost*
885697
days per year
Productivity losses*
431
$  M
Value at risk*
437
$  M
Avg. failure risk*
58
%
FTEs unblocked**
327707
days  per year
Producitivity gains**
159
$  M
Risk reduction**
157
$  M
Avg. risk reduction**
36
%
Heading
Heading
Employee category
10001+
Market cap
Large-cap
Revenue category
$1B to $10B
Sector
Healthcare
FTE days lost*
95745
days per year
Productivity losses*
47
$  M
Value at risk*
832
$  M
Avg. failure risk*
58
%
FTEs unblocked**
35425
days  per year
Producitivity gains**
17
$  M
Risk reduction**
300
$  M
Avg. risk reduction**
36
%
Heading
Heading
Employee category
1001-5000
Market cap
Large-cap
Revenue category
$1B to $10B
Sector
Utilities
FTE days lost*
29545
days per year
Productivity losses*
14
$  M
Value at risk*
861
$  M
Avg. failure risk*
58
%
FTEs unblocked**
10931
days  per year
Producitivity gains**
5
$  M
Risk reduction**
310
$  M
Avg. risk reduction**
36
%
Heading
Heading
Employee category
5001-10000
Market cap
Large-cap
Revenue category
$1B to $10B
Sector
Technology
FTE days lost*
51933
days per year
Productivity losses*
25
$  M
Value at risk*
846
$  M
Avg. failure risk*
58
%
FTEs unblocked**
19215
days  per year
Producitivity gains**
9
$  M
Risk reduction**
305
$  M
Avg. risk reduction**
36
%
Heading
Heading
Employee category
10001+
Market cap
Large-cap
Revenue category
$10B+
Sector
Basic Materials
FTE days lost*
491004
days per year
Productivity losses*
239
$  M
Value at risk*
626
$  M
Avg. failure risk*
58
%
FTEs unblocked**
181671
days  per year
Producitivity gains**
88
$  M
Risk reduction**
226
$  M
Avg. risk reduction**
36
%
Heading
Heading
Employee category
10001+
Market cap
Large-cap
Revenue category
$1B to $10B
Sector
Financial Services
FTE days lost*
181530
days per year
Productivity losses*
88
$  M
Value at risk*
767
$  M
Avg. failure risk*
58
%
FTEs unblocked**
67166
days  per year
Producitivity gains**
33
$  M
Risk reduction**
276
$  M
Avg. risk reduction**
36
%
Heading
Heading
Employee category
10001+
Market cap
Large-cap
Revenue category
$10B+
Sector
Consumer Cyclical
FTE days lost*
953682
days per year
Productivity losses*
464
$  M
Value at risk*
379
$  M
Avg. failure risk*
58
%
FTEs unblocked**
352862
days  per year
Producitivity gains**
172
$  M
Risk reduction**
137
$  M
Avg. risk reduction**
36
%
Heading
Heading
Employee category
10001+
Market cap
Large-cap
Revenue category
$1B to $10B
Sector
Technology
FTE days lost*
129360
days per year
Productivity losses*
63
$  M
Value at risk*
789
$  M
Avg. failure risk*
58
%
FTEs unblocked**
47863
days  per year
Producitivity gains**
23
$  M
Risk reduction**
284
$  M
Avg. risk reduction**
36
%
Heading
Heading
Employee category
10001+
Market cap
Large-cap
Revenue category
$1B to $10B
Sector
Consumer Cyclical
FTE days lost*
1501341
days per year
Productivity losses*
730
$  M
Value at risk*
90
$  M
Avg. failure risk*
58
%
FTEs unblocked**
555496
days  per year
Producitivity gains**
270
$  M
Risk reduction**
32
$  M
Avg. risk reduction**
36
%
Heading
Heading
Employee category
10001+
Market cap
Large-cap
Revenue category
$10B+
Sector
Consumer Cyclical
FTE days lost*
790328
days per year
Productivity losses*
384
$  M
Value at risk*
440
$  M
Avg. failure risk*
58
%
FTEs unblocked**
292421
days  per year
Producitivity gains**
142
$  M
Risk reduction**
158
$  M
Avg. risk reduction**
36
%
Heading
Heading
Employee category
10001+
Market cap
Mid-cap
Revenue category
$10B+
Sector
Consumer Cyclical
FTE days lost*
497614
days per year
Productivity losses*
242
$  M
Value at risk*
585
$  M
Avg. failure risk*
58
%
FTEs unblocked**
184117
days  per year
Producitivity gains**
90
$  M
Risk reduction**
210
$  M
Avg. risk reduction**
36
%
Heading
Heading
Employee category
5001-10000
Market cap
Large-cap
Revenue category
$1B to $10B
Sector
Consumer Defensive
FTE days lost*
52877
days per year
Productivity losses*
26
$  M
Value at risk*
799
$  M
Avg. failure risk*
58
%
FTEs unblocked**
19564
days  per year
Producitivity gains**
10
$  M
Risk reduction**
288
$  M
Avg. risk reduction**
36
%
Heading
Heading
Employee category
10001+
Market cap
Large-cap
Revenue category
$10B+
Sector
Healthcare
FTE days lost*
358811
days per year
Productivity losses*
175
$  M
Value at risk*
641
$  M
Avg. failure risk*
58
%
FTEs unblocked**
132760
days  per year
Producitivity gains**
65
$  M
Risk reduction**
231
$  M
Avg. risk reduction**
36
%
Heading
Heading
Employee category
10001+
Market cap
Large-cap
Revenue category
$10B+
Sector
Technology
FTE days lost*
859258
days per year
Productivity losses*
418
$  M
Value at risk*
390
$  M
Avg. failure risk*
58
%
FTEs unblocked**
317925
days  per year
Producitivity gains**
155
$  M
Risk reduction**
140
$  M
Avg. risk reduction**
36
%
Heading
Heading
Employee category
1001-5000
Market cap
Large-cap
Revenue category
$1B to $10B
Sector
Real Estate
FTE days lost*
17317
days per year
Productivity losses*
8
$  M
Value at risk*
807
$  M
Avg. failure risk*
58
%
FTEs unblocked**
6407
days  per year
Producitivity gains**
3
$  M
Risk reduction**
290
$  M
Avg. risk reduction**
36
%
Heading
Heading
Employee category
10001+
Market cap
Large-cap
Revenue category
$10B+
Sector
Consumer Defensive
FTE days lost*
415654
days per year
Productivity losses*
202
$  M
Value at risk*
605
$  M
Avg. failure risk*
58
%
FTEs unblocked**
153792
days  per year
Producitivity gains**
75
$  M
Risk reduction**
218
$  M
Avg. risk reduction**
36
%
Heading
Heading
Employee category
10001+
Market cap
Mid-cap
Revenue category
$10B+
Sector
Consumer Cyclical
FTE days lost*
462677
days per year
Productivity losses*
225
$  M
Value at risk*
581
$  M
Avg. failure risk*
58
%
FTEs unblocked**
171190
days  per year
Producitivity gains**
83
$  M
Risk reduction**
209
$  M
Avg. risk reduction**
36
%
Heading
Heading
Employee category
10001+
Market cap
Large-cap
Revenue category
$10B+
Sector
Energy
FTE days lost*
443792
days per year
Productivity losses*
216
$  M
Value at risk*
586
$  M
Avg. failure risk*
58
%
FTEs unblocked**
164203
days  per year
Producitivity gains**
80
$  M
Risk reduction**
211
$  M
Avg. risk reduction**
36
%
Heading
Heading
Employee category
1001-5000
Market cap
Large-cap
Revenue category
$1B to $10B
Sector
Real Estate
FTE days lost*
47212
days per year
Productivity losses*
23
$  M
Value at risk*
780
$  M
Avg. failure risk*
58
%
FTEs unblocked**
17468
days  per year
Producitivity gains**
9
$  M
Risk reduction**
281
$  M
Avg. risk reduction**
36
%
Heading
* LOSS ASSUMPTIONS: Based on a VaR (Value at Risk) of 34% (R&D) to business transformation (70%) and 82% (M&A) averaged to 58% (Dellermann 2020, McKinsey 2018). All calculations are based on R&D investments, CapEx and acquisition investments. The average company employs around 20% managers who spend 37 percent of their time making decisions, of which 58 percent are inefficient; each manager works for 220 days, (1760 working hours), and receives an average salary of €107k (McKinsey 2019). All data from publicly available annual reports 2022.
** OPPORTUNITY ASSUMPTIONS: Based on a risk reduction potential of 36% and an efficiency improvement potential of 37% (Dellermann 2020).
course roadmap

Four sessions to next-level decision making

part 1
01

Problem framing

We’ll help you to discover the most critical decisions for optimization to define the scope of your journey to outperforming decision-making.

Decision audit
2 hours
part 2
02

Use cases scoping

Our decision specialists help you optimize your decision-making process, define the required insights, data, AI services and tasks, and create a custom decision template dedicated to your needs.

Decision engineering
2 hours
part
03

Decision engineering

We deliver your fully customised dedicated instance of DeOS, onboard your team and data and guide your team to let you experience the full power of decision optimisation in action and create your success story.

DeOS pilot
2 hours
Kick-off &
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Validated
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Go Live &
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Decision optimzation system

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DeOS decision templates standardize everything from data to actions with best-practice business knowledge built in, so you can get started with a single click.

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Use our enterprise value calculator to work out exactly how much money you are leaving on the table — and how much you could stand to gain by transforming how you make high-stakes decisions with DeOS - the Decision Optimization System.

High-stakes investments (M&A, R&D, business model transformation etc.)
in millions $ / annually
0
200m
Business analysts, strategy consultants and data scientists working for those initiatives
FTE
0
200 Empl.
Average cost per full time employee in this role
in thousands $ / annually
0
200 K / year
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Explore decision-centric services

DeOS decision templates empower business users to apply AI-powered insights to how they make all kind of high-stakes decisions — without having to switch between tools.

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Hedge Fund Portfolio Monitoring
Capital Structure Optimization
Asset Sale
Strategic Alliance
Asset Acquisition
Transformation Initiative Priorization
Asset Valuation
Platform Ecosystem
Investment Target Screening
Earnings Allocation
Hedge Fund Portfolio Allocation
Price Target
Risk Monitoring
Exit Strategy Evaluation
Investor Sourcing
R&D Portfolio Performance Monitoring
Take-Privat
Enterprise Capital Allocation
Asset Price Optimization
Make-or-buy - purchasing
R&D Portfolio Optimization
CapEx Initiative Priorization
Fairness Opinion
Joint Venture
Credit Risk Monitoring
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Budgeting
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R&D Partnership
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Divestiture
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Sell-side Avisory Opportunity
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Debt Restructuring
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Project Financing Structuring
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Buy Side Advisory
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Financial Planning
CapEx Investment
Secondary Buyout (SBO)
Market Risk Monitoring
Market Index Monitoring
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Better M&A performance requires better decisions

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Manual work, siloed data, and biased decisions cost your business millions of dollars - every single year.

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