In a hospital in West Virginia, a nursing leader was trying to come up with a simple way to explain scientific thinking to his clinical staff. All of a sudden he said, "It's easy as XYZ." What he came up with was a simplified interpretation of scientific thinking that he calls XYZ Thinking. This can be a useful teaching concept for hospitals and other organizations practicing the Toyota Kata approach or other approaches to developing scientific thinking.
2. Scientific thinking can be powerful
Practitioners of the Kata
approach, which is based on
the research done by Mike
Rother, know that scientific
thinking can produce huge
results for our organizations
by helping us tackle those
big business challenges that
we don’t know how to solve.
3. But there are barriers to developing
scientific thinking in our companies
Just using the terms ‘science’ and
‘scientific thinking’ themselves can be
off-putting to traditional business
leaders who may not see how science
can have practical business application
“Run an experiment? So, we’re
going to put on lab coats and play
with some Bunsen burners and
whatnot? Uh, no thanks.”
–traditional leaders everywhere
4. Can we offer business
leaders a practical view
of scientific thinking?
5. Even though medicine is a
highly scientific pursuit, the
business of healthcare is not
typically managed in a more
scientific manner than other
industries.
But recently, in a hospital in Huntington,
West Virginia, a nurse leader practicing
the Improvement Kata was striving to
incorporate more of a scientific approach
into his team’s daily care coordination huddle. After
trying to define scientific thinking, he said…
“Well, it’s as easy as XYZ.”
6. The nurse leader
came up with this
‘XYZ Thinking’
image as a way to
simplify the concept
of scientific thinking
for his clinical staff.
Let’s break down
the XYZ concept…
7. • X indicates the action that we think will produce
the result. X is the intervention.
• We want to be rigorous about X, meaning that if in
the care coordination huddle we identify the next
step as X, then at the follow-up huddle we need to
diligently confirm whether X was done or not. This
maintains the integrity of the experiment.
• If X is not done as planned, that’s an opportunity
to do root cause analysis. Was our next step
impractical? Are there issues hindering execution?
Be rigorous
with the X
8. • Y indicates the result that we think will be
produced by the experiment. X + Y = hypothesis.
• We want to be objectively curious about Y,
meaning that if at a team huddle we decide to run
an experiment, then at the follow-up huddle we
should mainly be interested in whether to reject
our hypothesis or not. Very cut-and-dry.
• If the result we observe is something other than Y,
that’s not cause for making excuses, assigning
blame, or denying the evidence; instead let’s learn!
Be curious
about the Y
9. • Z indicates an unexpected result.
• We want to be excited about Z, meaning that the
team should not be deflated about getting an
unexpected result. Rather, we should treat this as
a highly successful experiment that will lead to
valuable learning.
• The focus should be on the learning, and when this
is the case, it creates an environment conducive to
innovation and striving for big business challenges.
Be excited
about the Z
11. Healthcare example of XYZ Thinking
The care coordination team predicted
that if the physical therapist rounded
(at least enter the room) on the patient
every day this week…
…then the patient would be more
likely to participate in therapy and
meet the care plan goals…
…and the PT did indeed round on the
patient every day, but the patient was
only able to receive therapy on 2 days.
12. Typical healthcare issues w/ X
Bad example: “Hey, PT, you’re going to
help the patient meet the care plan
goals, right?”
In healthcare, we often fail to establish a clear-cut,
verifiable next step, and will only focus on the
outcome, thus leaving it to the clinician to be
accountable for results. This predictably leads to
excuses, blame, & denial (or best-case, a hero
mentality).
13. Typical healthcare issues w/ Y
Bad example: “We can’t predict when
or if the patient will meet the care plan
goals. Every human is different.”
In healthcare, we are often hesitant when it comes to
predicting how a patient will respond to treatment,
because indeed every human is different. But this is
only an issue if we expect the “blame & shame game”
when we make a prediction that turns out to be
inaccurate. This (justified) hesitancy prevents us from
experimenting and learning.
14. Typical healthcare issues w/ Z
Bad example: “We weren’t able to
achieve the care plan goals this week.
Let’s keep trying and stick to the plan!”
In healthcare, we often don’t have the time nor
inclination to stop and study the situation whenever
we get an unexpected result. Plus, if we failed to
setup a good experiment w/ a testable hypothesis on
the front-end, it’s difficult to do much analysis on the
back-end. This deprives us of the opportunity to
extract maximum learning from each step.
15. These issues are engrained in the
way we think. To overcome them and
achieve XYZ Thinking, we must
practice new ways of thinking.
What’s one way we can incorporate
more practice of XYZ Thinking into
your team’s daily work?
18. About Michael Lombard
Michael Lombard, MBA, PMP, is an
accomplished leader in Lean
Healthcare, currently serving as
the Senior Director of Operational
Excellence at Cornerstone
Healthcare Group in Dallas, TX.
Contact info:
michael.g.lombard@gmail.com
@mikelombard
https://www.linkedin.com/in/michaelglombard