I'm Biljana Besker,
and I'm a JMP Account Executive for Global Premier Accounts.
My colleague Sarah Springer
and I will introduce you today
on how to become an analytic advocate in your company
and what resources we have available at JMP to help you get there.
So let's start.
What defines an analytics advocate?
The analytics advocate must be an advocate and a change agent
who spreads the analytic strategy and fosters an analytic culture
that everyone is comfortable using data -based insights
to improve the quality and effectiveness of their decisions.
Five characteristics to look for in an analytical advocate are,
They are trusted and well respected because of a proven track record
of managing difficult projects to successful completion.
And they have empathy because they listen to
and addresses fears and resistance to change
as new steps are taken on this unfamiliar path.
And of course, they are problem solvers.
They are willing to roll up their sleeves and work to overcome technical
and cultural challenges that arise through each stage of implementation.
They always show commitment.
They support the analytics strategy
and promote consistent interpretation of the goals for analytics.
And they are flexible.
Data-driven decisions require ongoing evaluation of their effectiveness.
An analytics advocate must recognize
when the part of the analytic strategy is not working,
and work with all parties to redefine the solution.
What is considered to be the analytics advocate's role?
As an analytical advocate, you must promote data as a strategic asset
and you have to address resistance and promote collaboration.
And there is a big need to promote a culture of evaluation and improvement
and to educate and empower the workforce.
So assets do not necessarily have essential value,
and assets are associated with liabilities.
So how to promote data as a strategic asset?
Analytic is about having the right information and insight
to create better business outcomes.
Business analytics means leaders know where to find new revenue opportunities
and which product or service offerings
are most likely to address the market requirement.
It means the ability to quickly access the right data points
to find key performance and revenue indicators
in building successful growth strategies,
and it means recognizing risks before they become realities.
So how can you address resistance?
There are three levels of resistance you must overcome.
The first and most important level is the C-Level resistance.
Preparing the technical infrastructure for an effective analytic program
may require significant resource investment for an unknown return.
This should be addressed where possible
with a small project recurring minimal infrastructure
to secure a quick win with positive expected ROI.
If this is not possible,
then show examples where others in the same industry have benefited.
Second is the Department- level resistance.
Process owners may resist the perceived effort
associated with data governance processes needed to make data cleaning
sufficient to support analytics.
The analytic s advocate must find ways to show how such efforts will result
in recurring long -term benefits to the organization
that will turn in regards and recognition for the Department.
Again, quick-win projects can help.
However, the analytics advocate should not stop there.
Important tasks are best accomplished with a dependable ally,
with shared interests.
And last but not least, we have the Front-line worker resistance.
As with business process owners,
front-line workers are not interested in extra work as we know
if it's not reflected in the metrics used to assess their performance.
A smart analytics advocate address that question,
what is in for me?
Integrating analytics solution into existing workflows
reduces incremental effort and empowers front-line workers
to make more informed decisions and improve job performance.
So how to become an effective advocate of analytics?
As an analyst, you are obviously aware of the power of data analysis.
You know that the application of appropriate analysis techniques
to a well constructed, meaningful data set
can reveal a great deal of useful information,
information that can lead to new opportunities,
improvements and efficiency, reduction in costs and other advantages.
While many organizations have adopted analytics on a wide scale,
several others still employ it only in certain areas,
and some, believe it or not, rarely use it at all.
If you often get excited thinking about new ways of applying analytics
in your organization
and are eager to share your excitement with people
you think would benefit of analytics,
you are in a good position to become an analytics advocate in your company.
focus on the person's greatest challenges and most burdensome tasks.
Everyone has something about their job that is source of frustration,
no matter how much they love what they do.
For the person you are working with,
a meaningful application of analytics is one
that relieves his or her frustration or minimizes it as much as possible.
As long as the application is also important to the overall business,
this is a great way to begin to show someone the true value of analytics.
It's also a good idea to start small
and then work your way up to bigger projects later
so that you are not overwhelmed
and thus don't run the risk of not being able to deliver.
Second is incorporate their knowledge and expertise.
You may be an expert on the application of analytics,
but you are most likely not an expert
on every functional area of your organization.
Not even the CEO can make that claim.
Therefore, you must rely on the insight of others
to help you understand all of the complexity
that cannot be contained within the data set,
including any legal, ethical, or other considerations
that must be taken into account.
What's more, you are demonstrating respect for their specific knowledge,
which will help build trust and make them more eager to work with you.
Third, learn to speak their language.
Being able to understand and communicate in the terminology
used by the people you are working with
will demonstrate that you are willing to meet them on their terms.
It's not a two -way street.
However, avoid using analytical
and statistical terminology as much as possible .
If necessary, practice finding ways to explain difficult
or complex concepts in an easy to understand manner.
Metaphors often work well for this.
Fourth, publicize your victories and show the credit.
Sorry... and share the credit.
Once you have successfully completed the project, be sure to tell your boss .
Ask him or her to spread the word
throughout the organization and externally if possible.
But make absolutely sure
that the credit is shared with those assisted you in the project.
This will help build attention to the power of analytics
within the organization.
As well as make those people you've just worked with
feel rightfully appreciated and respected.
If you look closely at these four recommendations,
you'll notice they all have one thing in common.
They put the focus on what you can do to help others.
Whatever you follow these specific tips or not,
as long as you promote the use of analytics as a service
that can help a person solve a problem that is important to them,
you will go a long way towards fostering a positive attitude
toward analytics throughout your organization.
But how to become a successful advocate of analytics?
Put user experience first .
it can be tempting to overlook the role of the end- user
and focus solely on business outcomes,
which is why the analytic advocate must ensure
that the focus remains on the value and overall experience for end- users
in addition to the positive business outcomes
the company wants to achieve.
To bring us back to our earlier discussion of low adoption and analytics strategy
that does not consider the user's position and needs
is at risk to become a strategy that is technically capable
but not valuable enough to keep users engaged.
To mitigate this risk,
the analytics advocate must be able to explain both:
the benefit of the analytics strategy to the business,
but also ensure that the strategy is beneficial for the end- users
who need to make business decisions.
And push the analytic strategy to evolve.
Of course, user and business requirements change over time.
So once the strategy is launched, the analytic advocate must ensure
that the strategy evolves to meet those demands .
Without repetition , the strategy runs the risk of outliving,
its usefulness and driving adoption rates down as a result.
Instead, the analytic advocate must monitor, manage,
and drive the strategy forward
to ensure ongoing utility at maximum business value.
Companies who want to introduce an analytics strategy
can make themselves much more likely to achieve success
by putting that strategy in the hands of someone who can understand end-users
and push the project to improve experiences and business outcomes.
Who understands the analytic represents a journey and not a destination.
Successfully appointing an analytic advocate
is the first step in this process.
Let me summarize what we just learned.
At the most strategic level,
analytic allows organization unlock latent value from their data
to gain insights, accomplish business objectives, and improved profits.
While these insights should empower everyone in the organization,
many organizations resist the cultural changes needed
to benefit from an analytic program.
As first step, executive leadership must establish
and support the analytics strategy.
Then , designate an analytic advocate to engage stakeholders
to unify that vision, understand and address pain points,
overcome resistance to adoption,
and demonstrate the value from analytics through quick win projects.
All organizations can better accomplish their mission of leverage and analytic
with a data -driven decision process.
Using analytics to achieve a sustainable competitive advantage
and generate significant return on investment
begins with a well -convinced analytics strategy and roadmap for success
that is aligned with and supports the overall business strategy.
And with that said,
I would like to hand over to my colleague Sarah Springer,
who will show you how JMP can help you
to become an analytical advocate in your organization.
Hi, I'm Sarah Springer.
Biljana, thank you so much for providing that great overview
of what makes a good analytic advocate within an organization.
I'm going to look a little more closely at a couple of those areas
that Biljana touched on,
and we're going to talk about a process and some tangible resources
that will assist you and your organization in building a culture of analytics.
So how can JMP support your organization in becoming more analytical
and how can we support an analytics advocate?
So we've outlined a process here to help you accelerate
your organization's analytics growth curve.
So that process is going to go through a couple of steps.
So first, we're going to talk about how to build a team of data ambassadors.
We're going to talk about the best way and some resources
to identify key use cases and define success.
We're going to talk about how to establish an efficient data workflow,
how to educate and what resources we have available
to educate and upskill yourself and your colleagues,
how to socialize your analytics successes,
and then how to democratize data and the process.
So Biljana touched on this in her presentation.
But what is in it for you?
If you're an analytics advocate within your organization,
what can this do for you as an individual?
You can be a vision setter and a change- agent
throughout your organization.
This is an opportunity for you to make a real impact on the lives
and the well being of the people in your organization.
You can be a subject matter expert.
If you identify a specific problem or a specific area of deed
and upskill yourself in that area.
You can really be looked at as an SME within your organization ,
and gain some recognition for yourself
within your organization and within the JMP community.
You'll be gaining credibility.
You'll become a leader in teaching others
the skills that you've learned and upskilled on.
And then ultimately,
we've seen a lot of our analytic champions throughout all of our organizations
really have a strong resume and advance in their careers
because of the great work they've been doing at their organizations
in building a culture of analytics .
Data is everywhere.
Analytics is an important competitive tool.
And it's really past the point of being able to not have analytics
embedded in your organization.
And so what we've seen is individuals
that have been in analytics advocate within their organization
have been quite successful , and so this is a real opportunity for you.
But what Biljana mentioned is it's really also about helping others
and making an impact on your organization and the world around you.
And so what's in it for your organization?
Advocates play a key role in demonstrating value and ROI .
You're able to pick a project,
a real challenge that you or your organization is having
and show the true value of the impact
that analytics can play to your organization.
Adoption of JMP or an analytical tool or an analytical culture can really help ,
again, bring the organization into the digital transformation age.
It is at the point right where we can no longer not take advantage
of all of this data that we have .
And so in this role you have a real chance to make an impact at your organization,
and again impact your organization's bottom line,
save your organization money by improving processes or producing less waste.
Other use cases we've seen are securing time -to -market
and you're really helping your company to stay competitive.
So the first part of the process, as you're thinking,
how do I make an impact at my organization is to think about, as Biljana mentioned,
who can come along with me in this journey?
Who else is feeling the same pains?
Who else can benefit from a strong analytic culture?
So looking beside you into other departments, but then also up.
Who at the executive level?
What executive sponsor might be interested in some of these pain points I'm having?
How can I get stakeholders to support this movement?
How can we get buy -in early?
And so the goal is to find reliable, passionate, accountable people
that are maybe having some similar challenges as you
to walk through this journey with you and to help,
as Biljana mentioned,
show the value and prove to leadership and prove to stakeholders
that this work is valuable and deserves attention and investment.
Once you have your colleagues and you have buy -in and you have your team,
what we want to do is the next step of the process
is really looking at identifying key use cases
and defining success.
So what success looks like is an important part
of defining an analytics strategy .
Thinking about some common use cases within your organization,
maybe you have too much data, maybe there's data not being used,
too many systems to get the job done, not a good way to share decisions,
maybe there's a lot of wasted time being able to sift through of all of that.
So figuring out what is my organization's challenge?
What would success look like?
How can I move the needle?
And as Biljana mentioned, starting small is important.
We want to think maybe of something that's not a huge undertaking,
but maybe has a broad impact.
So as you're thinking of the right place to start,
these are some things to consider .
Some great resources that I would recommend
as you're thinking through this,
if you want to look at your organization's annual report or 10-K,
if you're a public organization,
or maybe there are some internal documents that are outlining for the year,
what your risk factors are as an organization?
You can get a strong overview of some of the concerns
that executive leadership has
about maybe some of the risks that they could approach this year.
Often, we see some risks across R&D and manufacturing
that might be very relevant to being able to solve that problem with analytics.
Maybe it's time- to- market.
Maybe it's improving any sort of defects in the manufacturing process , right?
Those are things outlined in your organization's 10-K
or your annual report.
And that could be a really great win for you, right?
If you can pull some folks together
to want to solve one of those problems or improve one of those processes.
The other resource I would recommend taking a look at is
going to the JMP website and looking at our customer success stories.
There's a whole library across industry and challenge
that could really get your wheels turning and give you some great ideas
about some possible use cases and what success might look like.
So once you have your team and once you have the goal,
next you want to think about how to create and establish an efficient data workflow.
So it's important that you're able,
in order to do great analysis, you want to have good data access.
You want to be able to streamline that process.
How are you pulling, analyzing, and sharing that data?
How are you getting the right information to the right groups?
Where is your data?
Is it accessible?
Is there anything you can automate?
Can you make anything easier?
Can you use JMP Live to share information?
So there's a lot of things to take a look at.
Tangible resources for this include conversations with IT.
Maybe you can look at possible scripting or automation
within JMP or within your analytical tools
to really make an impact, to make this as easy as possible
so that it's in the hands of the right people
who can solve these real problems
and contribute to your success and the success of your organization.
So next, we're going to talk about
a step that is very close to my heart, training and upskilling colleagues.
I spent some years at SAS within SAS education,
helping JMP users do just this.
And so I wanted to touch on,
once you have your team, you define your goals,
you've got your data access in a good spot.
We want to talk about how do we give our team and employees and users
the tools and the knowledge to execute this plan.
What we're finding...
There was a survey done by HR Dive studio ID and SAS
that was conducted in October of 2020 .
And they found that this is a huge need.
88 percent of managers said they believe
their employees' development plans needed the change for 2021.
A lot of this was coming out of us shifting into a pandemic world
and people working remotely .
And folks are really asking for training and for development and for help.
Out of the survey,
50 percent of managers said, employees needed more upskilling,
more reskilling, and more cross-killing .
And 41 percent of the employees themselves said the same thing.
And that when considering the types of skills employees should focus on,
employees needed more technical skills.
They really , really want to build their skill set.
And so as you're thinking about how to build an analytics culture,
training and upskilling is really important.
And people are wanting those more technical skills
so that they can make a contribution in this age of digital transformation.
So the survey also brought to light
five major learning and development trends.
So I just wanted to highlight this as something to be thinking about
as you think about your strategy.
The trends were that companies are now expected
to take on more responsibility for employees and society,
and making sure that they're getting what they need,
that people are being taken care of .
And companies need to match...
Another theme was that companies need to match their technological investment
with the learning and development of their people.
Learning and development are much more universal,
and it's really a strong recruiting and retention skills.
And again, these hard skills are really in demand.
And so as you're thinking about your strategy,
it's so important to think about
how can I help my colleagues, my organization,
get the right knowledge and training in their hands
so that they can really be impactful with all this data that we have.
So here at JMP, we have a couple of resources I want to point out
that can be really powerful to help upscale your organization.
The first that we're going to touch on is the Statistical Knowledge Portal.
Then , we're going to take a deeper dive into STIPS,
which is our Statistics Course.
It's a free online course called
Statistical Thinking for Industrial Problem Solving.
It is award- winning, and it is self- paced,
and a wonderful resource that many of our customers are using
to provide analytical development to their employees.
And then finally, we do have some formal SAS training and some resources
that I do want to point out as we go through this process.
So the Statistical Knowledge Portal is a great site.
I've put the link there for you
that has information in all of these different areas that I've listed.
So it's a great way if you have somebody that needs to know a very specific skill,
they can go on here.
They can pull some resources and skill up fairly quickly.
It's a great way to get them started, to get their feet wet,
to develop some knowledge, to get some tips and tricks.
I would highly recommend spending some time on this website.
And then you, as the analytics advocate, can really help drive the person
to what skill they might need based on your project.
So I think there's a lot of collaboration that can happen here.
But I do want to point out that this is a phenomenal free resource
on the JMP website
and has a lot of great statistical information for you.
The next one I want to point out is STIPS.
So all of these modules that are on the right are self- paced.
They're deep- dive d into the topic area.
They are hands- on exercises .
And it's really going to help you get up to speed
and understand that statistical concept.
So as you're working on your project, as you're working towards your goal,
think about different areas of this course that might be helpful.
There is a great overview module at the beginning as well that I would
recommend that talks about what different processes you can use
to begin to be thinking statistically throughout your organization.
So it starts at the beginning, and then it goes all the way down
to advanced modeling, so it can really meet you where you are.
And we'll talk a little bit more about this course.
So what I love about this course is this is really something that JMP has put out
because they want folks to be strong in analytics
and they want folks to understand statistics
and to understand the why behind what we're doing.
And so we've put out some additional
resources to help companies upskill their teams.
So you can take this course in a self- paced format.
But we've had many, many customers want to use these materials in a different way.
We have customers doing lunch and worn
throughout their organization, having sessions where they'll take
a specific concept from the course and have discussion groups.
We have professors and universities using steps or some of this material as
prerequisites or even within their statistics courses.
And so what we've done is we've made
teaching materials that has put some of this material into PowerPoint slides
for you to use at your organization for some internal training.
And we wanted to make that easy and accessible for you.
So going to jump.com/ statistical thinking,
there's an online form on the right hand side of the page where you can fill
that form out and get these materials to use to help upskill your team.
And then finally,
the third training resource I wanted to touch on is Formal SAS Training.
SAS has incredibly strong, relevant trainings, hands- on trainings
that provide a real great depth and understanding of different concepts.
So there's lots of different formats for individuals, large groups, small groups.
And I've put the link up here so you can go check out those courses as well.
It's a really great way to upskill your team and then make sure
they have the right tools.
And if you don't know where to start, I definitely wanted to highlight a tool
that Fast Education offers called the Learning Needs Assessment.
It's a data driven survey that can be distributed to your team according
to learning area of what major areas that we often see our customers needing.
Maybe the major courses that SAS Education offers around design of experiments
or scripting or a Novel regression.
These are great resources.
And if you don't know where to start,
we want to be able to survey your team, identify what their preferred learning
style is, identify their competency in these areas,
and then put it in a report that's easy
for you and managers and executive leadership to understand.
And then we would work together with you to make great recommendations.
And those recommendations could be use of steps,
it could be use of formal training, it could be complimentary resources
from the Statistical Knowledge Portal,
but it helps give you an idea of where to start
if you're not quite sure according to your project and your goals,
what your skill gaps are, sometimes you need a little help identifying those.
So that's what this is for.
So once you've got your team upskilled, once your team is trained in the areas
and you're working on your project, it's time to document those successes, right?
Biljanna touches on this as well.
You want to be able to document that as a proof of concept,
show the value to your organization,
continue to get that commitment and investment in your work,
your team's work, in the power of analytics,
continue to help your organization move towards digital transformation.
And so being able to document these successes are important.
A couple of resources that I've found helpful to do this,
I think the main one is our customer success program.
We do have a great program, I mentioned earlier,
where you can get these stories published on the website,
but we've also helped some organizations with internal stories.
Ask your account team for help.
We want to help you document these successes,
and so we can certainly help you do that.
And then often we can help you do that
if you want to tell a story in JMP,
we would love to help you show the impact that you've made for your organization.
And then finally being able to democratize data in the analytic process.
So this is one of those steps.
How can we take what you've done
as a group and then spread this further throughout your organization?
Once you've done this and you've documented your successes,
I'm sure you're seen as effective as a leader,
you're probably well respected.
So now you get the opportunity to make even broader of an impact
on your colleagues and bring them along with you
in that success and make an impact on your organization.
So what you can do from here is
really empower more people to be more data- driven.
And I think using things like I mentioned with some of the steps tools,
maybe you're leading lunch and worms, maybe you're creating a user group,
maybe you're doing an internal newsletter about the power of analytics,
maybe you're working with the JMP team to do doctor's day in sessions
or different sessions around features
that have been very helpful to you with your project.
So this is your opportunity to help others,
and help others at your organization make an impact,
and help your organization shift to be more data- driven
in today's digitally transformed world.
So I want to leave you with some tangible next steps.
We've gone through a process of how to build a culture of analytics.
And as the next step,
JMP has a great resource, jmp.com/advocate,
where you can go and learn more about each of the steps that we've outlined today
and what resources are available to you that corresponds each step.
So today has been a great overview,
but if you do want to take a tangible step to move towards an analytical culture
within your organization, I would highly recommend that you go here
and check it out and then don't hesitate to reach out to your account team.
We're all here to help and we want
to support you in making an impact at your organization and around the world.
Here are sources for your viewing pleasure.
And I just want to thank you very much for your time and attention today.