What is Missing? - What WAS Missing? If the analytics tools are so good, why don't they make the decisions, control the actions and explain why and why not?

1. Copyright 2015, Compsim LLC, All Rights Reserved 1
Advanced Analytics:
What is Missing?
Or
What “Was” Missing?
A Compsim Whitepaper
Abstract
If your analytics tools are so good, why don’t they actually MAKE the decisions?
Organizations are always looking for ways to improve. Improvement can come
from many directions; reducing costs, improving operational capabilities,
improving products or services. For the past decade Information technology
suppliers have hyped “Business Intelligence” (BI) tools and “Big data”. Business
intelligence tools have focused on collecting, interpreting, and organizing
information so their clients (the decision makers within the organizations) can
make better business decisions. In other words, the tools were: “decision aids”.
Big Data has been the term used to define the location and distribution of
available structured and unstructured data that is commonly referred to as
“data in the cloud” today.
The two faces of organizations: First, they are viewed by their clients as
operational entities. It is almost as if the organizations have a mind of their own
and the organizations are the purveyors of the products and services. They do
not consider that it is the people within the organizations that are using
manpower and tools to deliver the products and services in the name of the

2. Copyright 2015, Compsim LLC, All Rights Reserved 2
organization. The ultimate consumers of the products and services of an
organization view the organization in this abstract way. So, for example, GM
delivers cars, and Google delivers search capabilities. The second face: the
organizations are viewed as a human hierarchy. Named individuals within the
organizations make the decisions, build the products, and/or deliver the
services. Purveyors of BI tools and cloud services target the second face. It is
this same human face that investment groups validate when they assign value
to the organization. It is this group that also makes the errors; they apply
personal biases, get tired, cut corners, violate regulations, procrastinate, fail to
respond in a timely manner, form inappropriate relationships, violate laws, give
preferential services contrary to stated policies, etc. Every human has drivers
that are contrary to the stated goals of the business.
This paper suggests that technology exists today to take the next step, which is
the active interpretation of the data and the active decision-making (adaptive
command and control) that can accelerate the decision-making process and
remove (or at least expose) human biases that may not be appropriate for
public, commercial or governmental organizations. Core to this capability is the
necessity to make decisions and actions that are 100% explainable and
auditable, so that the policies driving the decisions can be tuned / adjusted
when necessary.
The Problem
Many organizations have a Mission Statement that presents an internal and
external view of the boundaries of the organization. They may even have a
Vision statement that suggests how they will apply their capabilities to meet a
need that will exist in the future. These statements (if they exist) target human
consumption. We suggest that, in most organizations, employees have never
studied their company’s mission or vision statements. Therefore they have never
considered how those statements and goals should impact their behavior.

3. Copyright 2015, Compsim LLC, All Rights Reserved 3
Most organizations talk about continuous improvement. They hire consultants
and/or form teams to search for areas of improvement. Over time, the “low
hanging fruit” will have been picked. They invest in new tools based on the
topic of the day. Over the past decade BI and Big Data have gotten a lot of
exposure and much of the hype. At a lower level, the focus has been coding
solutions using distributed IF THEN ELSE processing. This can almost be viewed as
outsourced processing, or moving processing to where it can be managed
cheaper.
The target problems (addressed by BI and the cloud) are those that Dr. Horst
Rittel (UC, Berkeley) labeled “Wicked Problems” in the 1970s. Dr. Rittel
differentiated wicked problems from “Tame Problems” by suggesting that tame
problems are those where you can obtain a correct answer by writing a formula
to describe how the components of the problem are combined to get a correct
answer. Wicked problems are those where you are looking for the “best
response”; where it would not be economically feasible (maybe impossible) to
develop a formula to get a correct answer. He was a city planner. He
suggested that running a city could not be accomplished by writing formulas.
The Common Solution
Solutions that are commonly proposed today suggest that (as Dr. Rittel
suggested) if you can accumulate all information associated with a problem (all
the positions, with all the pros and all the cons of each) that a “reasonable
person” should be able to make the best decision. (Paraphrased from Dr.
Rittel’s paper1)
Much of today’s work has focused on the interpretation of unstructured
information using text analytics tools. BI tools collect, organize, and present
information for human consumption. This ultimately leaves the final decision-
1 Rittel, Horst; “Issues as Elements of Information Systems”, Working Paper No. 131, July 1970,
University of California Berkeley

4. Copyright 2015, Compsim LLC, All Rights Reserved 4
making up to the humans. Unfortunately those humans have other drivers that
may be unrelated to the stated business objectives. With the present analytical
tools, there is no way to isolate the human from the actual decisions, unless one
can remove the human from the decision-making process.
The Challenges
So, this leads to the following questions:
If the analytical tools are so good, why don’t they actually make the best
decisions (without depending on the human-in-the-loop)?
Why don’t the systems package their decision-making rational in a format that
the humans can audit (human-on-the-loop rather than human-in-the-loop)?
Why can’t organizations explain their value system?
• How important is profit?
• How much is at risk?
• How important is a new product in achieving the business objectives?
Why aren’t all decisions and actions explained with mathematical precision,
thus avoiding problems associated with the English language that may have
only general levels of compatibility from one person to the next?
• How warm is warm?
• How much stress?
• How much need?
• How much value?
• How important?
• How much risk?
Why can’t an organization provide a mathematically explicit explanation of
“what was considered” in any decision or action? If this explanation was

5. Copyright 2015, Compsim LLC, All Rights Reserved 5
available, they would also be able to see what was not considered in the
decisions and actions.
The Evolution of Technology
Man created machines to increase speed, increase strength, and to increase
quality; essentially to do more with less in order to amplify human capability.
Today many products and services cannot be delivered without the use of
machines. Computers are the machines for processing information. Computers
manipulate information by integrating and reformatting that information to
satisfy some need. Information is sensed, transformed, moved, integrated and
sometimes interpreted. We are moving towards a time when some information
will never be touched or observed by any humans. While there are those that
will reject this concept, it is happening. At the present time, much of this
information is lost, but as its value is recognized, technology will expand to fill the
gap. All information, even incorrect information, has value. If incorrect
information can be detected, the problem can be fixed.
A Military Example
Perhaps a military example can help explain how advances in technology may
translate from a military application into the commercial space.
Today everyone knows about drones. They are perceived by some as
autonomous systems. At this time, in most cases they are simply remotely piloted
vehicles that are driven by humans. But this picture will change in the near
future. When you consider that policies are being developed for machines to
make the ultimate decision about who and what to target, it is easy to
understand that the complexity of this type of decision is comparable to (or
even more complex than) the decisions associated with running a company.
First, it is not acceptable to allow an unmanned combat aerial vehicle (UCAV)
to have a bad day, wait too long to make a decision, or to violate international

6. Copyright 2015, Compsim LLC, All Rights Reserved 6
law. In combat where the fog of war complicates the decision-making process,
humans are given some latitude. Errors are made. But when policies are
executed by machines, far less latitude for human-like errors will be accepted.
Also, when policies are created for machines to make life and death decisions,
they will be mass-produced. Those policies must be correct and enforceable,
because those responsible for the policies will be held responsible in a court of
law. This means that for a machine to execute the policies they must be
packaged in a mathematically explicit manner. Everything that the UCAV does
must be reviewed.
The problems faced by the UCAV are not unlike those faced by employees of a
company. Once you get past the elementary problems, human-like judgment
and reasoning are required to interpret the complex, inter-related sets of
information. The UCAV must make time critical decisions to 1) do something or
refrain from doing something (shoot or don’t shoot), 2) choose from mutually
exclusive options (select the most appropriate weapon, choose the most
effective tactical maneuver, and 3) allocate resources (apply the right amount
of power to each of the control surfaces, use the right amount of weapons
balanced against evaluated collateral damage, balance the tactical value of
the observed target with target validation, and mission importance). And, like
the human decision-maker in an organization, the situation is likely to change.
Decisions are not likely to be made in isolation. They will be based on a
hierarchy of information sources, where each situation is changes.
In terms of speed the decisions, actions and reactions of a UCAV must be
performed much faster than those made in the corporate executive office
today (using today’s executive decision-making speed as a comparison). The
complex, life and death decisions made by the UCAV must be made in
milliseconds. This doesn’t mean that they are any less complex. What it does
mean is that the public has a higher level of expectations from a machine than
they do from a human.

7. Copyright 2015, Compsim LLC, All Rights Reserved 7
Events over the past few years have highlighted the failure of human-in-the-loop
systems where the response to adversarial actions have resulted in mass
casualties. Militaries around the world are coming to the realization that they
have to react faster to survive.
The Question
So the question remains: Why should the public expect more from its automated
warriors than from corporate management?
The Answer
One would suggest it should not expect more! The public should know that
companies behave ethically, make appropriate use of their resources, and
make the best decisions for their customers and their shareholders.
So why haven’t all the organizational and operational decisions been
automated by now? We have the BI tools and access to all the information in
the cloud, yet industry has refrained from taking that next step.
One reason is that there is a general lack of trust in machines making decisions.
At least that is what is stated, yet we trust in all the products that are made by
machines. We eat food created by machines. We are transported by
machines. We are entertained by machines. We are monitored by machines
for our safety.
There is also resistance from decision makers. Making decisions is what they are
compensated for. But what happens if their stock holders demand a better
level of service? Will they relinquish their high paid jobs to a machine that could
do the job better? Will they accept inputs from machines that can
automatically analyze all the data continually and advise the decision maker of
the optimal time to make the big decisions?

8. Copyright 2015, Compsim LLC, All Rights Reserved 8
Perhaps there are some enlightened executives that want to lead their
organizations into the future…?
The Suggestion
Compsim’s Knowledge Enhanced Electronic Logic (KEEL®) Technology2 enables
the capture, test, packaging, explaining and auditing of human-like judgment
and reasoning for deployment in microcontrollers. For example: KEEL
Technology can be used in Unmanned Combat Aerial Vehicles and
conventional computer systems, such as those executing BI tools. When human-
like judgment and reasoning are packaged in a mathematically explicit
manner, systems can make complex decisions, just as if the decisions and
actions were made by the humans that created the policies. The added
benefit is that the decisions and actions are easily interpreted by humans. The
KEEL Dynamic Graphical Language exposes the value system used in the
decision-making process. Automatically generated influence diagrams show
exactly what was considered in making the command and control decisions.
Rather than subjective “shoot from the hip” decisions, effort is expended
auditing, and expanding the decision-making model to take into account new
knowledge and understanding of the market.
When an organization uses KEEL Technology, they are making organizational
decision-making their core competency. They are packaging their decision-
making models into reusable / automatable policies that can be continually
extended as the business changes. Automated systems can monitor changes in
technology, marketing practices, the economy, political situations,
environmental considerations, and be prepared for change by capturing “how
to think” rather than how to follow a set of rules. This allows systems to respond
to surprise situations they have never been programmed to respond too.
2 KEEL Technology; http://www.compsim.com/About_KEEL.htm

9. Copyright 2015, Compsim LLC, All Rights Reserved 9
Stock holders will grow to expect that executive decisions are exposed to audit
and are not biased for personal gain.
Summary
Technology exists today to begin capturing organizational decision-making in a
manner that can be automated. First it will be delivered as an executive
augmented management function. Then, as organizations capture their
decision-making skills in formal automatable policies, executive management
models can be retained as a corporate competency. That competency can
be extended over time to provide continuous improvement and avoid the
delayed and biased decisions that crepe into organizations today. Eventually
organizations will be transformed to the state where corporate policy engineers
refine and extend the policies with better intelligence and a better
understanding of the core competencies of the organization.
Bottom Line: Organizations (commercial and governmental) that fail to test the
water now with augmented decision-making models now will be left behind
and will be rejected by their customers (and by their stockholders who demand
that the best products and services are offered in the most cost effective
manner).