Dashboards And Data Analytics (annotated)

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Transcript of Dashboards And Data Analytics (annotated)

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For 4 of the past 6 years while commuting to client sites in Chicago, this

dashboard informed me about:

• My Speed (MPH)

• Distanced Traveled (Miles)

• Fuel Status (Full, Almost Full, Half Tank, Almost Empty, …)

• Outside Temperature (degrees F)

• Fuel Economy (MPG)

This dashboard alerts me

• about engine trouble

• if someone in the front 2 seats is not wearing a safety belt

I interpret these descriptive statistics and apply meaning based upon stimulus

and situation as I travel.

For example, if I see a speed limit sign or the flicker of red & blue lights, I check

the carrot stick on the speedometer.

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In July of 2014, my family and I moved to Memphis. On the first morning of my

commute, I had 2 questions:

• Where am I going?

• How do I get there?

With the following 2 words, I am able to access answers:

OK GOOGLE!

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Today I say, “OK GOOGLE drive to work”.

OK GOOGLE delivers a dashboard to answer my commuting inquiries

regardless of current location.

I can even ask where coffee may be along my route.

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I like to plan ahead.

I like to minimize risk.

I like to choose the best route.

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OK GOOGLE uses data mining and learning analytic capability to investigate

factors such as Road Traffic Patterns and Road Traffic Density.

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OK GOOGLE renders dashboards that provide me a choice of optimized routes.

OK GOOGLE and I have such a great relationship now that each weekday

morning it proactively renders a dashboard for me.

This dashboard provides insights such as predicted time of arrival along the

route I choose to take each day. These insights even indicate hazards along my

route.

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Sam Cooper is part of my preferred route. After a few commutes, I observed

how the City of Memphis raises revenue.

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New friends such as Navmii and Waze provide dashboards with audio visual

cues about my speed in relation to the posted limit.

I can share in real time road conditions, hazards, and I’m told one can share the

location of Memphis’ Finest.

These applications utilize social media, data mining, and analytic learning

techniques to share insights during my commute.

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I began my relationship with dashboards seeking information and now rely on

these dashboards to answer questions, allow me to investigate alternatives, and

inspire me to make choices and take action.

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The teams that collaborate to produce these dashboards apply:

• Descriptive Analytics to calculate rates such as MPH to inform.

• Diagnostic Analytics to answer inquires by association and correlation.

• Predictive Analytics to investigate patterns.

• Prescriptive Analytics to inspire action by presenting optimized choices.

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These organizations develop and facilitate the capability to calculate, deduce,

model and learn.

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These teams seek to fit and evolve organizational culture to improve performance through

actions inspired by data driven insights.

The culture word cloud above shows important cultural elements to consider when fitting

dashboards & data analytics with culture.

Think about your organization.

• Is it driven by performance?

• Do Leaders have the insights necessary to define strategic targets?

• Can Decision Makers access insights to determine tactics to meet these targets?

• Can Operators take action from optimized choices presented in their view on their device?

• Are Analysts enabled to mine quality data and create insights that inspire action?

Everyone has a commuting story. Whether on the highways or taking action to set goals,

decide what to sell, improve student progress, or treat a patient.

Using analytics we develop d dashboards that share insights like these shown through the

following examples.

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The purpose of this dashboard is to explain to leaders profit margin performance. These insights utilize descriptive analytics to inform.

When developing dashboards, it is important to:

• understand the context (Profit Margin Performance)

• apply appropriate visual display (mix of explanation, metric values, and bar chart providing data and insight to leaders)

• eliminate clutter (every element on the dashboard has a purpose; here the grey background is used to reduce distracting luminous effect when presented on a large digital screen)

• focus the viewers attention (black background is where the eye focuses first; we use the black background to focus the attention on the insights)

• Design! (utilize graphic design techniques or collaborate with a designer; here the color blind palette is used so that potential audience members who are color blind can gain full insight from the bar chart)

• tell a story (this dashboard flows from understanding company performance, to understanding current regional performance, then provides historical perspective to understand trends.

This dashboard is created to be reproduced without need for continual manual intervention. The sentences are formulaic (not hard coded). When metric values and data change, the insights update based upon time frame chosen.

From these insights we see that South and Central regions profit margin performance decreased when compared to last year. South and Central region decision makers are interested in how they can improve performance to meet the profit margin strategic target set by leaders.

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The purpose of this dashboard is to respond to decision maker questions

regarding profit margin performance. These insights utilize context customized

metrics and click-to-drill diagnostic analytics to answer inquiries.

A blue color palette with white background is chosen to provide a comforting

experience while providing bold cues for emphasis (discount).

The story is organized from left to right and back forming a natural reading Z

pattern familiar from reading and scanning documents. Decision makers are

informed about regional profit margin performance relative to the prior year, can

inquire about the relationship between profit margin, sales, and discounts sales

managers apply to encourage customers to buy. Profit margin performance by

product categories and subcategories are presented to provide insight into how

profit margin performance aligns with products sold.

Where is the Central Division losing profit?

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The Central Region VP of Sales can click on the Central region name or bar on

the Profit Margin Trend chart (upper left) to focus the view on the Central

region.

Sales increased across the region but profit decreased. Profit decreased

minimally in furniture, is flat in office supplies, and increased in technology.

When choosing office supplies to drill into the subcategories, Binders reveal a

large decrease in profit margin and aligns with the maximum level of discount.

The Central Region VP notices that office supply products with higher discounts

correlate with profit margin declines.

This decision maker is inspired to ask analysts to determine the relationship

between profit margin and discounts.

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The analysts develop an exploratory dashboard to investigate the relationship between profit margin and discounts.

These analysts are enabled with descriptive, diagnostic, predictive, and prescriptive analytic capability. These analysts are trained to develop reproducible insights. These analysts know the value of designing dashboards to investigate context relevant factors spanning relevant parts of the organization by designing reusable processes.

This dashboard is designed as an application for analysts to apply diagnostic and predictive analytics to determine relevant factors for choosing tactics.

The story is revealed across three panes left to right. Analysts can filter factor combination, see detail by product category and subcategory for this year and the comparison year. Analysts utilize transactional order data to fit a trend function showing the resulting profit margin when discounts are applied.

The result of this investigation inspires the Central Region VP to sponsor the development of a dashboard that assists sales managers to calculate discounts that meet or exceed profit margin target set by leaders.

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Analysts, decision makers, and operators collaborate and apply easy to scale,

reproducible, repeatable processes to develop a model to predict profitable

discount by product.

The process is expressed in a human readable model and process work flow.

This process utilizes applications and tools based upon common technology

platforms easily integrated across applications to provide my insights, in my

view, on my device, to inspire me to act and improve my performance.

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Sales managers now have the Discount Advisor, a mobile application providing

capability for sales managers to apply profitable discounts based upon product

and quantity. These discounts can be maximized for win-win customer

relationship. Customers enjoy discounts. The organization enjoys profits.

Organizations can store the decisions made and compare to prescribed advice

when reviewing performance.

Sales managers are able to make decisions and take performance improving

action in the flow of their work just as easy as utilizing OK GOOGLE to find

optimal commuting routes while traveling.

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To inspire performance improvement, create dashboards that inform, inquire

investigate and inspire actionable strategic, tactical, operational, and

performance insights by applying descriptive, diagnostic, predictive and

prescriptive analytics.

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