CASE STUDY# 2:
INSIGHTS ANALYTICS: TECHNOLOGY FOR A KNOWLEDGE MANAGEMENTPROGRAM.
What did Gupta and Arun Sharma identified regarding KM techniquesafter
brainstorming with members of leadership? (CLO#6)

CASE STUDY# 2:
INSIGHTS ANALYTICS: TECHNOLOGY FOR A KNOWLEDGE
MANAGEMENT PROGRAM
Pawan Gupta was worried. He had just been appointed the head of theknowledge management
(KM) team at a leading analytics firm, Insights Global Analytics,in May 2019. Before he
became head of the KM team, Gupta led the global-level corporate KMinitiative at a leading
knowledge process outsourcing service provider. Before that, he wasa KM technologist at a
global management consulting firm, where he developed Web-basedknowledge maps, search
tools, and custom KM tools. Insights Global Analytics handled manyinternal analytics
processes and projects. Most of its projects required extensivedomain and statistical expertise
to provide meaningful insights to clients. Employees with prioranalytics experience had skill-
sets, techniques and heuristics that could be utilized for otherprojects. Likewise, analysts and
consultants working on business research projects had strong domainknowledge about the
various technological trends acquired over a long time. They coulddecipher the story and
signals behind the numbers stored in various databases. However,sometimes one team did not
know about the rich skills possessed by another team, thus forcingthem to rely on a less-than-
optimal skill set.
To address this issue, the top leadership team envisaged creating aKM platform that could be
used to promote a knowledge-sharing culture within Insights GlobalAnalytics. However, the
leadership team was not sure about the technological options thatcould achieve this objective.
Different technological options had different functionalities,benefits and costs of ownership.
Gupta’s main challenge was to select technological options thatwould help to create a cost-
effective and successful KM platform.Accordingly, Gupta beganestablishing a KM platform for Insights Global Analytics. Hegave
himself three months to assess the various technological optionsand then present his assessment
to the top leadership team. With the team’s approval, Gupta wouldestablish an integrated KM,
information and communication program. The program would be limitedto a few teams initially
before it was extended to the entire organization. Later, computersand tablets division, printers
division, corporate marketing and data center business by analyzingand interpreting
organizational data to facilitate data-driven decision making. Itwas the analytics unit of one of
the world’s largest technology companies by revenue, and was amongthe world’s top 50
valuable brands. Insights Global Analytics had 700 employees,mostly PhDs, MBAs, chartered
accountants and statisticians from premier educational institutesin India and overseas for
solving problems related to business decisions, planning, businessintelligence optimization,
supply chain planning, Web analytics and marketing strategysupport.
The success of any analytics project was dependent on providingquality insights based on the
data analyzed. Depending on the complexity of a business question,teams worked together to
integrate statistical and business knowledge and to delivermeaningful insights. The top
leadership of Insights Global Analytics, being an internalanalytics unit in the knowledge-
intensive sector, knew that it had the employees and knowledge baseto stay ahead of stiff
competition from alternatives such as third-party vendors thatmight handle the outsourced
analytics work; however, the company lacked an effective avenue forsharing knowledge across
teams. Without a platform for sharing, employees faced difficultyin identifying which teams
or individuals could help them.
Insights Global Analytics also handled many processes using data toprovide regular insights
into markets, products and business operations. Employees involvedin the processes haddeveloped strong domain-specific knowledge andskills, such as automation to: reduce
turnaround time, minimize errors in data analysis and reporting,and improve productivity;
however, when they transitioned to new roles, the company oftenlost the employees’
automation and domain-specific knowledge crucial to interpretingdata and to employees
working on other teams. Daily operations showed the need for aplatform for sharing
knowledge.
Insights Global Analytics extensively used statistical tools suchas Excel, JMP and SAS, and
statistical techniques such as market-basket analysis andtime-series analysis. As the use of
advanced statistical tools and techniques was rarely taught inschools, many of the analysts who
joined Insights Global Analytics were interested in learning theseadvanced tools. As such, top
management felt that a KM program was useful as a platform foremployees because it would
allow them to post their learning queries to the statisticalexperts in the unit more efficiently.
Gupta came to Insights Global Analytics with a mandate to initiatea KM program platform that
would facilitate the sharing and documentation of organization-wideknowledge. He realized
that the market had abundant KM tools to use for documentation butthe success of the KM
program depended on whether employees perceived the knowledgesharing as useful — and
even fun — rather than as an additional burden. Gupta favored usingunconventional approaches
to KM implementation to include abundant tacit knowledge pertainingto analytics techniques
used for different processes and projects. In addition,conventional approaches would encounter
difficulty in documenting many of the heuristics involved inanalytics procedures. The Insights
Global Analytics workforce was highly skilled in terms ofeducational qualifications and
domain knowledge. If the KM program solely focused on documentingthe underlying
knowledge, it would use a technical jargon familiar to specificdomain specialists onlyEmployees who worked in other domains or whohad other skill-sets would find the program
incomprehensible, so its utility would be restricted to teamboundaries. Hence, the KM platform
would fail to achieve the primary purpose of enabling knowledgesharing across teams.
Gupta’s major challenge was to select cost-effective technologiesthat would facilitate and
promote knowledge sharing. He worked with Arun Sharma, a technicalleader who had
experience in Microsoft SharePoint, wikis, blogs and contentmanagement. Aware that Insights
Global Analytics had high expectations from the KM program, Guptaand Sharma pondered
their various technological options. With a few members of theleadership team and middle
management, they brainstormed and identified three broad options:(1) technologies already
used in the organization; (2) open source solutions; and (3) paidKM solutions. But at the same
time, both of them somehow feel that we have reduced the KM issueto a mere technical issue.
We are only discussing the functionalities of platforms and theircost of ownership. We are
confused about how these technological options by themselves willencourage the sharing of
knowledge. We must think beyond the platform and consider a mix ofoptions and initiatives
that will foster a knowledge-sharing culture.