1. 78i am scip Special Edition
Needs Assessment and Implementation Requirements
of a Knowledge Management System for Competitive
Intelligence Applications
by Paul Santilli & Stephanie Paulutt
BACKGROUND
It is a fact that is readily agreed upon throughout
the business community that technological advances
over the past 15 years have significantly changed
the way organizations operate. The most obvious
advance surrounds the meteoric rise of the Internet
and the never-ending generation of applications
developed to support the billions of users and their
information requirements. Similarly, Social Media
(SoMe) had jumped on the internet backbone and
now has proliferated into a dynamic communications
phenomenon that is unprecedented in history. Facebook
has 1.5 Billion subscribers, Twitter has 500 million
registrations, LinkedIn has 450 million users, Instagram
has 400 Million active participants - and they all are
growing in size, capability, and global presence.
Additionally, we are on the cusp of an explosive
tidal wave of data surrounding the Internet of Things
(IoT). IoT is all about connecting vast numbers of
“smart” machines and autonomous devices across
multiple platforms and applications in order to gather
information about the performance and usage of
products and services. Industry analysts are predicting
50 billion connected devices by the year 2020, all
transmitting mountains of information every second of
the day.
This new information landscape presents enormous
challenges for the Competitive Intelligence (CI)
professional – the scalability and analytical processing
capability of all of this data is simply overwhelming to
historical CI methodology and modeling behaviors used
in the past.
One of the key ways to prepare an organization for

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this onslaught of information is not by simply directing
more people towards the problem, but by looking at
the requirements from a holistic perspective; mainly
understanding the value of tools and related processes
that can be utilized within an organization to gain
better insights into data analytics. A key area to
explore is the use of Knowledge Management Systems
(KMS) designed for CI practitioners. Well defined,
these tools can be extremely effective in helping
organizations efficiently manage this data tidal wave
in a quick and seamless manner to arrive at better
actionable insights for quick organizational decision-
making for both strategic and tactical use.
What is a Knowledge Management System and why
does your organization need it?
A KMS system is a tool that collects and analyzes
information from a vast quantity of resources to
provide comprehensive intelligence on a real-time
basis. Some critical elements are:
• A platform used for creating, sharing and
organizing information and knowledge.
• Used as a central repository (similar to a data
library) based on harvesting relevant data with
real-time monitoring of web sources.
• Integrates different types of data sources and
formats
• Data is indexed and clustered to be searchable
based on user requirements.
• Proposes features and functionalities to analyze the
content, such as customized dashboards and related
user interfaces.
• Supports the generation of deliverables for sharing
across the organization.
KMS systems centralize data that is otherwise often
present in separate data silos, making analysis and
sharing difficult. It helps to exploit the full potential of
the knowledge present in an organization by making
the data available at a central location. This makes
it much easier to locate and extract relevant content
for the user. Additionally, info can be collected and
extracted real-time, without delays in compilation which
leads to shorter development of actionable insights
(Time to Insights (TTI)).
But how do you define such a KMS and what do you
need to consider?
There is a five-step approach for designing and
implementing a system for CI:
• Start with a needs analysis to gather the
requirements.
• Establish a process including the description of
responsibilities and the implementation plan.
• Define Key Performance Indicators (KPIs) and the
expected added value.
• Determine the Implementation and application
aspects toward CI needs.
• Establish a Value proposition and requirements
fulfillment assessment and Review.
NEEDS ANALYSIS
To determine the right context for a knowledge
management system you need to understand the
market dynamics and competitive positioning of your
business. In fact, this understanding and common
awareness represent the basis for everything that
follows. Being a critical element, this should receive
appropriate levels of time and attention.
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The key question is clear: what is it that the CI
practitioner needs to collect in order to make better
decisions for your organization?
Too many times, CI practitioners gather substantial
amounts of information for the sake of “data
gathering” without understanding how and why this
data is relevant to their objective. Understanding the
context of the data collection requirements and how
it is relevant to the objective of the CI practitioner is
an obvious but often overlooked first step in a needs
analysis.
All stakeholders should be considered in the needs
analysis and have the chance to express their
information needs, key topics, desired output, etc. in
order to best characterize objectives to drive tool
requirements. (One technique that can be utilized is
for stakeholders to recommend the preparation of a
catalogue of “open” questions allowing everyone to
describe the “ideal” tool by prioritizing their wishes.)
If the objective of the tool is to be used by different
divisions within an organization, it is important to detect
potential synergies and common needs at this stage.
For example, a list of use cases can help in illustrating
that the colleague in the office next door is looking
exactly for the same data as you.
Example of four divisions in an organization who might
have use cases in common:
PROCESS
Once the needs have been defined, the practical part
begins with the description of the process covering
the main responsibilities as well as the implementation
plan.
It is crucial to define precise roles and responsibilities
and make everyone commit to them. Ideally, all
stakeholders from decision-maker to the future KMS
end user should be represented here. An additional
key requirement is to ensure key solution enablers are
involved in the process definition, as well as technical
experts when it comes to content integration and IT
requirements. Early involvement by all key members at
this stage is critical, and allows for sufficient planning
and alignment of requirements to business objectives;
this includes developing realistic deadlines that also
allow certain flexibility with regards to time and
resource planning.
When it comes to the implementation plan, the
following main steps and milestones are required:
• Preparation of the official requirements catalogue
identified during the need analysis and summarizing
the use case and reason of setting up a KMS.
• Defining clear Key Performance Indicators and
evaluation criteria to assess the added value of the
KMS.
• Obtaining a precise understanding of knowledge
management systems available on the market and
make a preselection based on an RFI (request for
information). This should include defining a proof
of concept to test one or two tools against a set of
established criteria.
• Whereas analysts will assess the workflow and
functionalities of the tool, the CI practitioner should
think about positioning the KMS internally for
effective development of actionable insights, and
how to promote it within the organization as a cross-
functional strategic tool.
Use Case/ Topic Marketing
Corporate
Strategy
R&D
Business
Development
I want to detect new trends
at an early stage to assess
their potential.
X X
Which new technologies
should my company focus
on?
X X X
How can I optimize my
analysis on customer
satisfaction and my
customers’ (new) needs?
X X X
I want to combine external
& internal data to get the
full picture.
X X X X
>> Needs Assessment and Implementation Requirements of a Knowledge Management System for Competitive Intelligence Applications

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• During the KMS evaluation cycle, the IT department
should be involved to define the effective
implementation plan to deploy the system. The
latter actually requires a good understanding of
the organizational structure, culture and again the
market dynamics the organization is surrounded by.
KEY PERFORMANCE INDICATORS (KPI)
Just like other projects, the performance and success
of a KMS implementation is measured via KPIs. At the
same time, their definition is more challenging in this
context as classic indicators based on financial figures
only cannot be applied 1:1 here. It is important to
understand that KPIs associated with a knowledge
management tool are rather qualitative, and mid-term
/ long-term oriented.
One major indicator refers to an increase in efficiency
regarding the whole process starting with the collection
of data and ending with the actionable insights
generation and sharing. This mainly includes the
reduction of time spent on each step to have more time
left for analysis and interpretation. The centralization
of data is key in this context and the latter should be
available for everyone at any time.
Another indicator implies the relative ease at being
able to switch from a reactive approach to a proactive
one, directing the information collection towards the
anticipation of changes and disruptions. In other words,
the status of “being informed” which implies a look
back on published data shall change to a predictive
detection mode focusing on weak signals and change
indicators.
Besides, it is crucial to enrich the analysis and
deliverables regarding the depth and variety of data.
Thus, analysis and recommendations become more
comprehensive and ideally reflect a look beyond the
near-term tactical actions of the company to one that is
more strategic in nature.
Another KPI refers to encouraging a change in
company culture towards a natural sharing of data and
knowledge. Data silos should be reduced to a minimum
and be replaced by a policy of data centralization
and transparency. KMS systems help facilitate this
information sharing by proposing different system
functionalities that are easy to use not only for CI
practitioners, but can also be effective tools for other
organizations (Sales, R&D, etc.)
Lastly, it is important to define realistic deadlines for
the KPI achievement. Companies tend to underestimate
the cultural change they go through by implementing
and using a KMS on a continuous basis. Although
it is necessary to have so-called “Quick Wins“ to
justify the investment, the real advantage is the long-
term knowledge enrichment and continuous strategic
investment that these tools can support.
All in all, these qualitative indicators create an advance
in knowledge gathering and thus a competitive
advantage which will lead better analytics and
hopefully, a better business proposition.
IMPLEMENTATION
After testing and optimizing the tool for CI and
relevant KPI requirements, the implementation should
be focused on these 3 areas:
• Immediate departmental applications and business
requirements – determining the ability for the tool
to extract relevant content, in the right format,
and in a real-time progressive output to meet
departmental requirements and achieve short-term
objectives in data compilation and analytics. One
of the key areas to consider is not only the volume
of data sources, but the ability to manage the data
sources to include key areas that are vital to your
CI analytics objectives – those sources that are
rich in content and truly critical to getting the best
information as possible. Sometimes these sources are
readily available, but sometimes there are sources
that require memberships and login credentials
– having a tool that can navigate around feed
limitations and allow for credentials and related
access implications is a major advantage over
traditional secondary research methodologies.
• Development of actionable insights from tool
output generation – data generation is important,
but the ability to develop actions from this data is
what is key. The tool must be able to segment this
information in order to visually identify key areas
that allow the CI practitioner to easily interpret
and readily develop action plans for strategic and
tactical application.
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5. 82i am scip Special Edition
• Leveraging of tool functionality throughout similar
organizations within the parent company – this is
an area that helps with Return on Investment (ROI)
and can leverage not only the learnings from your
organization, but to enrich the data collection
and analytics to include peripheral requirements
from potentially related businesses within your
organization.
VALUE PROPOSITION AND ASSESSMENT
REVIEW
Of course, as with any major system or tool
implementation, there needs to be measurements in
place to determine effectiveness and whether the
tool has met overall expectations and deliverables,
as outlined in the KPIs mentioned earlier. Every
organization will have different specifics on how well
the tool satisfied their needs, but there are some
foundational elements that are applicable to most
environments:
• Not just a large volume of data processing, but the
right data processed at the right time - secondary
research analytics is readily available and easy to
use, but KMS systems should bring a new dimension
to filtering information so that it is most useful and
most recent for up-to-date decision making on real-
time market and competitive activities. The whole
purpose of the tool is to equip the CI practitioner
with better information to react quickly to market
dynamics!
• Generation of actionable insights – this is another
key requirement; the information needs to not only
be significantly more valuable than traditional
secondary research sources, but also needs
to be segmented in a way that allows the CI
practitioner to easily navigate through the data
and realize tangible insights. This should allow
for quick interpretation and easy generation of
recommendations and suggestions for strategic and
tactical direction planning.
• Support and enhancements moving forward – not
all implementations are finite. There will probably
be additional requirements, changing business
conditions, and new learnings that will require
modifications to the KMS model. The ability for the
tool to allow for changes and the flexibility of the
development / ability to incorporate modifications
without major system upheavals are two other key
determinants for CI practitioners to consider.
Complex business market disruptions and changes in
market dynamics will lead to exponential increases in
data generation, and will put a great deal of stress on
Competitive Intelligence models. Practitioners will need
to be pragmatic in their data compilation and efficient
in their analytics to stay ahead of the competition.
Knowledge Management Tools are an effective means
to managing data work streams and provide a vast
array of valuable outputs and deliverables that will
lead to actionable insights for effective utilization in
organizational strategic planning.
ABOUT THE AUTHORS:
PaulSantillileadstheBusinessIntelligence
and Customer Insights organization for
Hewlett Packard Enterprise’s (HPE) WW
OEM Business, and has been with HPE for
20 years. He is responsible for Business and Competitive
Intelligence Modeling and Customer Insights analytics,
where he is the Chairman of HPE OEM Executive
Customer Advisory Boards worldwide. Paul also is on the
Strategic Competitive Intelligence for Professionals (SCIP)
Board of Directors and has presented worldwide on
various topics related to CI in both keynote and workshop
forums. Paul has a Bachelor’s degree in Engineering from
the University of Michigan, and a Master’s degree in
Engineering and Business from Stanford University.
Stephanie Paulutt
Stephanie brings 10 years of experience in
Market and Competitive Intelligence with
roles as a Web Intelligence Analyst, Project
Manager, and Sales Manager for leading
informationandintelligencesoftwarecompaniesinFrance
and Germany. This year Bertin IT brought Stephanie on
board as Sales Director for its Digital Intelligence Solution,
AMI Software. Stephanie is responsible for business
development in the DACH region (Germany, Austria,
and Switzerland) where she supports her customers in the
introduction and implementation of the AMI platform
as well as associated processes and workflows. Stephanie
holds workshops and delivers presentations on CI tool
implementation at a variety of conferences and as a guest
lecturer at the University of St. Gallen in Switzerland.
>> Needs Assessment and Implementation Requirements of a Knowledge Management System for Competitive Intelligence Applications