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DPBS1190 Data, Insights and Decisions
创建日期：2024-05-15 18:14:54
标签： DPBS1190
Data, Insights and Decisions

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DPBS1190

Data, Insights and Decisions
Week 9.1 – Design and Agile Thinking
In our last two lectures on design and experimentation,
we discussed about the different research designs
including the experimental research. This lecture will
focus on:
• role of human-centric design based approaches in
big data analytics projects
• principles of design thinking to business analytics
• agile analytics development
Algorithms do not create any value until they are
embedded in the business, which means moving from
an ‘analytics world’ perspective to a ‘business universe’
perspective.
The essence of design thinking is to approach
problems in a similar manner to the way designers
would.
It is a holistic approach that aims for innovation
(Brown 2008, 2015).
It involves using a designer’s sensibility to satisfy
user requirements, based on technological
feasibility, with a possibility of making a practical
business strategy, creating a prospective market
and adding value for customers (Brown 2008).
According to Martin (2009), two common perspectives
prevail regarding how to create value in a business.
One perspective attaches importance to ‘analytical thinking’,
logic, and certainty.
The other emphasizes ‘intuitive thinking’ and ‘raw creativity’.
The third option is using a ‘dynamic interplay’ between
these two views – namely design thinking.
Design thinking holds that neither analytical nor intuitive
thinking alone is sufficient.
Martin (2009) stresses that people need to use both kinds of
thought, but at different points in the knowledge funnel.

For many years, the work of Everett Rogers, a Professor
of communication studies has prompted companies and
researchers to think about why and how innovative
thinking spread in organizations.
The newness of an innovation may be expressed in terms
of knowledge, persuasion, or a decision to adopt. In this
digital economy of data-driven decision-making; many
companies that wish to be dynamic, innovative and growth
oriented have a unique opportunity to access the market.
Apple, for example, has shown the value of strong design
emphasis in product development.
Often strategic, technological, and organizational barriers
constrain the ability of companies to discover new
customer segments and business opportunities.
Incorporating design-oriented thinking and agile methods
into business analytics and technology strategies provides
knowledge derived from analytics that allows companies
to innovate their products, services, and processes.
In reality, most companies are still not utilizing or investing
in the available analytics to achieve competitive
advantage.
According to Martin (2009) CEOs may have the most
influence over an organization’s direction, but
developing your design-thinking skills is valuable and
productive , no matter what role you are in.
Martin(2009) advises:
“Take the lead in redesigning your company structure.
Rather than keeping people in set positions with specific
titles and known tasks – which is reassuring but
reliability-driven-consider organizing around projects and
functions, as design firms do. Redesign financial
systems. Rather than insisting on highly specific
budgets, set goals…..Don’t give the highest
performance awards to the most prominent
departments, but rather to those that solve the most
‘wicked’ problems”.
Design thinking is a five-step process. A description of
each of the five steps is provided by the Stanford design
school (d.school) and documented in a ‘how-to’ guide by
Doorely et.al. (2018). The following slides will outline the
work of Doorely et.al.
The five steps are:
• Empathize
• Define
• Ideate
• Prototype
• Test
Empathy is the foundation of human-centered design
process .
The Empathize mode is the work you do to understand
people, within the context of your design challenge.
It is your effort to understand the way they do things and
why, their physical and emotional needs, how they think
about world, and what is meaningful to them.
The goal of define mode is to craft a useful and
actionable problem statement to establish a point-of-view.
This should be a guiding statement that focuses on
insights and needs of a particular user.
Insights do not often jump into your lap, rather they
emerge from a process of synthesizing information to
discover and patterns.
The define mode is about sensemaking.
Ideate is the mode of the design process in which you
concentrate on idea generation. Mentally, it represents
the process of ‘going wide’ in terms of concepts and
outcomes.
Ideation provides a large repository of diverse ideas that
are the source material for building prototypes to test
with users.
A prototype can be anything that a user can interact with –
be it a wall of Post,-It notes, a gadget you put together, a
role-playing activity, or even a storyboard,
Ideally, you bias toward something, a user can
experience.
Walking someone through a scenario with a storyboard is
good, but having them to role play through a physical
environment that you have created will likely bring out
more emotions and responses from that person.
Test should be in the real context of user’s life.
For a physical object, ask people to take it with them and
use it within their normal routines.
For an experience, create a scenario mirroring the real-
life situations.
Testing offers to refine your solutions and make them
better.
For example, SAP uses design thinking to provide
insights into specific markets and to better understand
customer needs.
We introduce agile thinking as the ideal pedagogy to fully
utilize analytical capabilities in problem-solving and
innovation.
The Agile Scrum approach, developed by Ken Schwaber
and Jeff Sutherland in the early 1990s, mimics
contemporary software development practices to help
organizations struggling with complicated development
projects.
With its focus on solving problems through iterative and
incremental practices, Agile Scrum provides a flexible
framework that encourages meaningful collaboration among
teams.
Project requirements change over time, and solution
providers must adjust their solutions accordingly.
An agile approach explicitly embraces such changes and
sets out to create teams that are flexible and able to adapt
to emerging task requirements.
Various methods for agile development have been
adopted by industry, the most popular of which is Scrum
(www.scrumalliance.org).
Roles in Scrum (such as Scrum master and product
owner) entail powerful responsibilities that can be
adopted to bring structure within analytics projects.
Likewise, the ‘ceremonies’ of Scrum – which include
short daily meetings, planning meetings, review
meetings, and team retrospectives – all encourage
analytics teams to embrace face-to-face collaboration
where possible.
Scrum doesn’t focus on delivering just an increment of
business value; it focuses on delivering the highest priority
business value as defined by the customer (Product
Owner).
The Product Owner and the Team confer about what that
definition is, and then the Team decides what it can do in
30 days to deliver high-priority business value.
Thus the short feedback loop becomes a business
feedback loop – Scrum tests early and often whether the
system being developed will deliver value and exactly what
that value will look like.
This allows the system to be moulded over time to deliver
value as it is currently understood, even as it helps to
develop a better understanding of that value (p.xii).
(Mary Poppendieck in Schwaber 2004).
• Design thinking and agile are management practices
that play an important enabling role for the
development of new analytical tools to build operational
agility that helps firms to sense environmental changes
and to respond effectively.
• These methodologies have implications for
management styles.
• Management must acknowledge and promote such
new knowledge work, which represents different
approaches to problem-solving based on fundamentally
different epistemologies, i.e., emergence and
adaptation rather than top-down control.
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