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From YouTube: Value stream framework - summary
A
A
A
In
order
to
get
better
transparency
on,
what's
happening
with
the
stuff
that
they're
building
helping
users
to
visualize
once
they
visualize
the
value
stream,
helping
users
to
understand
where
items
might
be
stagnant
and
collaborate
with
their
team
in
in
in
with
regards
to
sort
of
moving
these
forward
tactically
in
real
time
and
then
once
the
value
stream
has
been
mapped
and
you
can
start
delivering
stuff
with
it.
You
can
start
reflecting
on
the
performance
and
how
the
trends
have
been
over
the
last
few
months.
A
We
deliver
this
much
in
revenue
or
we
can
get
this
much
profit
or
it
costs
this
much
in
order
to
do
that
so
connecting
connecting
everything
from
visually
visualizing,
the
the
value
stream
to
delivering
items,
as
well
as
reflecting
on
how
you
can
improve
your
workflow
and
finally
understanding
what
value
is
being
created
off
the
back
of
this.
So
this
is
an
overarching
sort
of
thing
which
helps
you
to
get
a
better
understanding
of
how
you
can
use
git
lab
in
order
to
ship
things
faster.
A
Now,
I
think
everyone
will
be
sort
of
familiar
with
the
gitlab
objects
and
gitlab's
life
cycle
and
analytics
is
sort
of
been
testing
out
various
strategies
for
where
we
want
to
deploy
analytics
and
we've
tested
out
a
few
things.
So
we
tested
out
object
level
analytics
where
we've
provided
analytics
around
issues
and
merge
requests
and
so
on.
A
We've
implemented
sort
of
more
stage,
develop
stage
type
analytics
where
we're
looking
at
particular
stages
and
looking
at
how
these
are
performing
in
the
key
metrics
within
these
stages,
and
then
we've
also
started
to
create
value
in
stream
analytics,
which
is
up
until
this
point
sort
of
allowing
users
to
map
the
custom
stages
of
their
particular
workflows
within
git,
lab
visualize
that
and
see
how
long
it's
taking.
Now.
We
want
to
move
this
forward.
Currently,
it's
a
minimal
maturity
and
we
will
actually
want
to
move
it
forward
to
a
viable
maturity.
A
So,
in
order
to
do
that,
we
think
we
should
be
trying
out
and
investing
more
time
in
these
particular
areas
of
deliver,
optimize
and
evaluate
each
one
of
these
areas
has
a
job
to
be
done,
aligned
with
it,
and
what
we
can
do
here
is
start
to
invest
more
time
and
effort
to
provide
value
for
users
beyond
just
mapping,
but
allow
them
to
tactically
look
at
things
in
their
value
stream.
Reflect
on
how
their
value
stream
is
performing
and
see
the
value
that's
coming
from
their
value
stream.
A
And
by
focusing
on
these
areas,
we
will
hopefully
be
able
to
create
user
flows
which
map
from
these
areas
to
value
stream
and
back
again,
as
well
as
the
fact
that
these
areas
will
be
the
most
polished
and
and
and
full
filled
with
with
features,
meaning
that
we
can
get
more
useful
data
off.
The
back
of
it,
so
that's
the
general
approach
we're
taking
and
to
sort
of
summarize
a
little
bit
more.
I
wanted
to
show
you
sort
of
how
value
streams
map
to
our
devops
life
cycle.
A
So
this
is
taking
something
like
a
feature
moving
it
through
the
process
and
finally,
shipping
it
to
production,
and
this
is
at
the
single
sort
of
value
stream
layer,
but
there's
also
the
layer
of
the
value
stream
network.
So
this
is
the
the
map
or
the
interdependencies
between
multiple
value
streams
within
an
organization
that
ultimately
sort
of
blend
together
and
provide
value
in
a
parallel
way.
A
So,
for
example,
we
could
have
gitlab
org,
have
its
own
value
stream
and
share
a
similar
way
to
this.
We
could
have
the
design
system
for
get
lab
pajamas
and
how
it
interacts
with
supporting
and
providing
components
for
gitlab
org
and
then
also
get
lab
ui,
so
the
actual
place
where
the
components
are
built.
So
it
would
be
really
useful
and
and
really
interesting
to
sort
of
visualize
and
see
the
interdependencies
between
these
value
streams.
A
A
I
can
also
see
it
being
used
as
a
way
to
sort
of
map
competitors
against
where
we
are
and
what
we're,
providing
and
potentially
also
used
as
like
a
canvas
and
a
workshop
activity
for
value
stream
mapping.
So
I
think
there's
a
lot
of
possibilities
off
the
back
of
this
and
I'd
I'd.
Love
to
hear
your
perspective
on
whether
this
has
clarified
anything
or
what
we
could
do
with
this.
So
thank
you
very
much
for
your
time
and
I'll
see
you
later.