birst webinar slides: "build vs. buy - making the right choice for a great data product"

Build vs. Buy: Making the Right Choice for a Great Data Product

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Presenter

ksmith@birst.com @kevinmsmith kevinmichaelsmith

Kevin Smith VP, Embedded Solutions

ksmith@birst.com

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What is a data product?

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A story of building analytics gone wrong

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Our missionMake our existing SaaS application more engaging by adding analytics

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We have smart Engineers… Let’s build it

ourselves and save some

money!

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We had resources.

I’m an analytics user story. Please implement me!

I’m an analytics user story. Please implement me!

I’m an analytics user story. Please implement me!

I’m an analytics user story. Please implement me!

I’m an analytics user story. Please implement me!

I’m an analytics user story. Please implement me!

I’m an analytics user story. Please implement me!I’m an analytics user story. Please implement me!

I’m an analytics user story. Please implement me!

I’m an analytics user story. Please implement me!

I’m an analytics user story. Please implement me!

I’m an analytics user story. Please implement me! + +

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We had a vision.

$ $ $ $ $

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What we actually got.

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Why was this so painful?

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The Truth about Buy vs. Build for Embedded Analytics

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The BI bar has been raised1

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Time has changed the analytics game

It’s on the web? NICE!

1990

It’s only 30 days old? NICE!

1995

I can sort by column headers? NICE!

2000

A chart? In color? NICE!

2005

Real-time data? NICE!

2010

I can’t drag this chart to a new location, apply filters and have it notify me when it exceeds the targets I uploaded? FAIL.

2015

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Because table stakes & delighters aren’t static

Table Stakes• Expected • Can’t compete here • Your competition

has them • Can’t charge for this • Increases over time

Delighters• Unexpected • The place to

compete • Useful for

differentiation • Can charge • Transition to table

stakes over time

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Delighters become table stakes

Table Stakes• Nice looking visuals • Drill down • Filter • Dimensions

Delighters• Personal settings • Customize • Notifications • Trends • Targets • Predictive • Annotations

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It will take longer & cost more than you expected

2

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We can build it for less!• Pay for Highcharts• Cost to build ETL• Cost to build SSO• Cost to build pages

Buildit year 1 year 2 year 3

• Possibly buy more storage

• Possibly buy more bandwidth

maybe $150K? +20K?

• Possibly buy more storage

• Possibly buy more bandwidth

+20K?

Our cost to build = $190,000 over next 3 years

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Buyit

Buying is expensive!

year 1 year 2 year 3

$250K

• Pay platform fee• Pay for

implementation• Pay for training

• Pay platform fee• Pay platform fee

$100K $100K

Our cost to buy = $350,000 over next 3 years

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Our cost to buy = millions and millions over an infinite timeframe

Buyit

Buying is, like, SUPER expensive!

year 1 year 2 year 3

$250K

• Pay platform fee• Pay for

implementation• Pay for training

• Pay platform fee• Pay platform fee

$100K $100Kinfinity

$100K times infinity

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• Pay for Highcharts• Cost to build ETL• Cost to build SSO• Cost to build pages

Buildit

Buyit

• Possibly buy more storage

• Possibly buy more bandwidth

year 1 year 2 year 3

• Possibly buy more storage

• Possibly buy more bandwidth

• Pay platform fee• Pay for

implementation• Pay for training

• Pay platform fee• Pay platform fee

$190K (but

probably even less)

Infinite money

Clearly, we should build it!

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What we all think we need to do…

Buy charting package

Build ETL

Build Charts

Build Dashboards

Connect via SSO

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In reality, there’s a bit more.Buy charting package

Build data load

Build Charts

Build Dashboards

Theming

Aggregate data

Build roll-ups

User permissioning

Admin pages

Multi-tenancy

Connect via SSO Filters

DimensionsTarget setting

Target setting

Transformations

UI controls

Drill down

Drill Across

QA

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$What are you skipping in order to build?

3

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Cost to build analytics

Cost to support analytics

Cost of NOT working on your

core application

The cost of missed core product value

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Your most talented people should work on unsolved problems.

50% of companies base their decision to build on the fact that they have the necessary talent to build analytics

From Wayne Eckerson, “Embedded BI: Putting Reporting and Analysis Everywhere”, TechTarget, December, 2014.

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Where can we add the most differentiating value?Ask

Core Product Analytical Platform

• Do we have all the features we need to solve the customers’ needs?

• Could we build features that differentiate us from the competition?

• Could we build functionality that would be hard to copy?

• Is analytics where we want to compete?

• Do we need to build the infrastructure in order to achieve this?

• Can we build BI functionality that is differentiating?

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Can you build what you need down the road?

Category Types of Analytics Questions Answered

Prescriptive • Optimization• Randomized testing

• What’s the best that can happen?• What happens if we try this?

Predictive • Predictive modeling/forecasting• Statistical modeling

• What will happen next?• What is making this happen?

Diagnostic • Data exploration• Intuitive visuals

• Why did this happen?• What insights can I gain?

Descriptive• Alerts• Query/drill-down• Ad hoc reports/scorecards• Standard reports

• What actions are needed?• What is the problem?• How many, often, where?• What happened?

SOURCE: Disambiguating Analytics, July 2, 2013, Sanjeev Kumar, International Institute for Analytics

SOURCE: Magic Quadrant for Business Intelligence and Analytics Platforms, February 5, 2013, Analyst(s): Kurt Schlegel, Rita L. Sallam, Daniel Yuen, Joao Tapadinhas

Cap

ability

Easy (er) to build

Hard to build

Much harder to build

YOU have to build this

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It’s hard to build fast enough to differentiate

4

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Two ways to compete on analytics

Differentiate (we’re the leaders!)

Neutralize (we’ve got BI too!)

Core Value Key Metric Main Challenge

Separation Unmatchable How far?

Comparability Good enough How fast?

Framework adapted from Reaching Escape Velocity, Geoffrey Moore, 2012

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Two ways to compete on analytics

Differentiate (we’re the leaders!)

Neutralize (we’ve got BI too!)

Core Value Key Metric Main Challenge

Separation Unmatchable How far?

Comparability Good enough How fast?

Framework adapted from Reaching Escape Velocity, Geoffrey Moore, 2012

Can you build fast enough to

differentiate?

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Build fast enough outrun the competition…

and STAY ahead

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Two ways to compete on analytics

Differentiate (we’re the leaders!)

Neutralize (we’ve got BI too!)

Core Value Key Metric Main Challenge

Separation Unmatchable How far?

Comparability Good enough How fast?

Framework adapted from Reaching Escape Velocity, Geoffrey Moore, 2012

Are you willing to cede your development

roadmap to the competition?

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The risk: your competition dictates your pace

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You need to make a balanced decision

5

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It’s an equation, not a single number

Total cost to

buy analytics

-Total

cost to build

analytics

≥Opportunity

cost of building

+Risk of not being able to execute now &

future

Cost Side Strategy Side

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It’s an equation, not a single number

Total cost to

buy analytics

-Total

cost to build

analytics

≥Opportunity

cost of building

+Risk of not being able to execute now &

future

What’s the TCO for

purchasing analytics

What’s the real cost to

build

What aren’t we doing if we build

and how important is it?

Will we be able keep up the

development pace for the foreseeable

future?

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1 The cost to buy embedded analytics

Total cost to

buy analytics

-Total

cost to build

analytics

≥Opportunity

cost of building

+Risk of not being able to execute now &

future

What’s the TCO for

purchasing analytics

What’s the real cost to

build

What aren’t we doing if we build

and how important is it?

Will we be able keep up the

development pace for the foreseeable

future?

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2 The real cost to build

Total cost to

buy analytics

-Total

cost to build

analytics

≥Opportunity

cost of building

+Risk of not being able to execute now &

future

What’s the TCO for

purchasing analytics

What’s the real cost to

build

What aren’t we doing if we build

and how important is it?

Will we be able keep up the

development pace for the foreseeable

future?

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Capture all of the true costsTask Type Task Title Description

Licensing Buy the software to make the visualsPurchase of the software to make the charts + maintenance & support for Hi Charts (10 developer license) -- this ONLY includes production

ETL Build connector to data source Create processes which will connect the charting software to the data source(s)ETL Perform transformations Transform the data into an analytic ready state for chartingData Modeling Create data aggregations Perform the roll-ups of data so that you can compare to previous yrs , qtrs, etc.UI Create dashboard page Create the page which will contain your analyticsQA Perform QA Inspect the analytics and all calculations for accuracyUI Create dimensions Create the dimensions by which measurement can be examinedData Modeling Create filters Create the filtering element to include/exclude data by dimensionData Modeling Build drill-down/across paths Link analytics together so that users can drill down and across to explore causesSecurity Build multi-tenancy model Develop model to ensure that customers can't see each other's dataSecurity Build security model Develop model to ensure that users see only the data they are allowed to seeData Create data model for targets Build a model to store targets for the metricsUI Build UI for target setting Create an interface to allow for the setting of targets by metricUI Build UI for alerts Create the interface for setting alers and notifications for user self-serviceData Modeling Create visualizations Build the visualizations to display the data such as bar charts, line charts, infographics, etc.

Data Modeling Create reportsBuild the pixel perfect reports that use the metrics and dimensions to display the data in a tabluar format with rollups, sub-groups, totals, etc.

Administrative Build user mangement capabilitiesCreate the functionality that allow you to add and remove customers and companies from the analytical functionality

Administrative Build monitoringDevelop the monitoring capabilities so that you can see the total usage by customer (for billing purposes)

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And calculate both money & timeVariable Value

Hourly rate $150.00# of data sources 2# of visualizations 15# of reports 2# of metrics 30# of dashboards 1# Dimensions/metric 2

Task Type Task Title Description QuantityHours per Item Total Hours Total Cost for Task

LicensingBuy the software to make the visuals

Purchase of the software to make the charts + maintenance & support for Hi Charts (10 developer license) -- this ONLY includes production 1 n/a n/a $3,600.00

ETLBuild connector to data source

Create processes which will connect the charting software to the data source(s) 2 20 40 $6,000.00

ETL Perform transformations Transform the data into an analytic ready state for charting 30 10 300 $45,000.00

Data Modeling Create data aggregationsPerform the roll-ups of data so that you can compare to previous yrs , qtrs, etc. 30 10 300 $45,000.00

UI Create dashboard page Create the page which will contain your analytics 1 20 20 $3,000.00

QA Perform QA Inspect the analytics and all calculations for accuracy 30 5 150 $22,500.00

UI Create dimensionsCreate the dimensions by which measurement can be examined 60 5 300 $45,000.00

Data Modeling Create filtersCreate the filtering element to include/exclude data by dimension 15 5 75 $11,250.00

Data ModelingBuild drill-down/across paths

Link analytics together so that users can drill down and across to explore causes 15 5 75 $11,250.00

Security Build multi-tenancy model Develop model to ensure that customers can't see each other's data 1 20 20 $3,000.00

Security Build security modelDevelop model to ensure that users see only the data they are allowed to see 1 20 20 $3,000.00

DataCreate data model for targets Build a model to store targets for the metrics 1 20 20 $3,000.00

The Powered by Birst Buy vs. Build Calculator

* not including the time to manage the project

$226,350

Building your dashboard in-house would cost at least:

that's 1485 hours or 0.67 FTE years not working on your core product

How much does it REALLY cost to build dashboards for your product on your own?

Your cost to build using these parameters

Our expected cost to build:

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3 Opportunity costs & risks of building

Total cost to

buy analytics

-Total

cost to build

analytics

≥Opportunity

cost of building

+Risk of not being able to execute now &

future

What’s the TCO for

purchasing analytics

What’s the real cost to

build

What aren’t we doing if we build

and how important is it?

Will we be able keep up the

development pace for the foreseeable

future?

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Four parts to this side of the equation

Can we build it FASTenough?

What ELSE could we build with the time?

Do we want to KEEPbuilding it?

Can we build it GOODenough?

1 2

3 4

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Can we build it FAST enough?

• Do you have the resources to build it?

• Can you build it quickly enough to meet demand?

• Can you build it fast enough to outpace the competition?

1

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Can we build it GOOD enough?

• Do we have the talent to build this?

• Can we get to the “delighter” functionality in the near term?

• Will we be able to meet the “table stakes”?

• Do we know what our customers need?

2

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Do we want to KEEP building it?

• Will we have the resource to continue to support this?

• Will we have the resources to continue to develop this?

• Will we be able to meet one-off requests and future table stakes?

3

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What ELSE could we build with the time?

• Is this as or more important than our core functionality?

• Are we willing to delay core product functionality to build (and maintain) analytics?

• Is this the best use of our resources - is this why customers buy our product?

4

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Use The Matrix

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Low Risk Medium High Risk

Can we build it fast enough?

We’ve got a development team dedicated to analytics, fully-trained in the entire stack, and can build quickly.

We have resources, but may have trouble building quickly enough to achieve table stakes.

We don’t have the resources/don’t want to dedicate the resources to build analytics.

Can we build it good enough?

Yes — we can build all the basics plus functionality to differentiate ourselves from the competition.

Maybe — we can add some table stakes, not all. Maybe our delighters will outweigh the gaps in functionality.

Nope — we’d have trouble getting to table stakes.

Do we want to keep building?

Yes — this is where we will compete so we’ll devote equal resources to analytics develop as our core app.

Maybe — we could add some functionality over time but it would secondary in importance to the core app.

No — we’d prefer to use our resources on other things.

Could we be doing other things?

No — analytics are the app for us. We consider this to be the core of what we do.

Maybe — analytics are important and our core app roadmap is not full.

Yes — we can add more value by working on our core application.

The Buy vs. Build Decision Matrix

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Low Risk (1 point)

Medium (3 points)

High Risk (5 points) TOTAL

Can we build it fast enough?

We’ve got a development team dedicated to analytics, fully-trained in the entire stack, and can build quickly.

We have resources, but may have trouble building quickly enough to achieve table stakes.

We don’t have the resources/don’t want to dedicate the resources to build analytics. 3

Can we build it good enough?

Yes — we can build all the basics plus functionality to differentiate ourselves from the competition.

Maybe — we can add some table stakes, not all. Maybe our delighters will outweigh the gaps in functionality.

Nope — we’d have trouble getting to table stakes. 3

Do we want to keep building?

Yes — this is where we will compete so we’ll devote equal resources to analytics develop as our core app.

Maybe — we could add some functionality over time but it would secondary in importance to the core app.

No — we’d prefer to use our resources on other things. 2

Could we be doing other things?

No — analytics are the app for us. We consider this to be the core of what we do.

Maybe — analytics are important and our core app roadmap is not full.

Yes — we can add more value by working on our core application. 2

GRAND TOTAL (possible 20 points) 10 points

The Buy vs. Build Decision Matrix

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Low (1 point)

Medium (3 points)

High (5 points) Our Rating Importance

(1=low to 3=high) TOTAL

Can we build it fast enough?

We’ve got a development team dedicated to analytics, fully-trained in the entire stack, and can build quickly.

We have resources, but may have trouble building quickly enough to achieve table stakes.

We don’t have the resources/don’t want to dedicate the resources to build analytics.

5 2 10

Can we build it good enough?

Yes — we can build all the basics plus functionality to differentiate ourselves from the competition.

Maybe — we can add some table stakes, not all. Maybe our delighters will outweigh the gaps in functionality.

Nope — we’d have trouble getting to table stakes. 5 3 15

Do we want to keep building?

Yes — this is where we will compete so we’ll devote equal resources to analytics develop as our core app.

Maybe — we could add some functionality over time but it would secondary in importance to the core app.

No — we’d prefer to use our resources on other things. 3 2 6

Could we be doing other things?

No — analytics are the app for us. We consider this to be the core of what we do.

Maybe — analytics are important and our core app roadmap is not full.

Yes — we can add more value by working on our core application. 2 3 6

GRAND TOTAL (possible 60 points)

37 points

The Buy vs. Build Decision Matrix

x =

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The Buy vs. Build Decision Spectrum

Consider building your own analytics

You likely will be able to build fast enough and

keep building fast enough to hold off the competition

Consider buying your analytics

It is unlikely you will get to market fast enough or be able to stay ahead of

your competition

Consider a combination strategy

You may be able to build fast enough and keep building fast enough to beat the competition in

select areas

Low Risk High Risk

The red zone

Medium Risk0 - 20 points 21 - 40 points 41 - 60 points

The yellow zoneThe green zone

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Weigh the pros & cons to make the decision that’s right for your situation

Cost Side

May save $53K

Strategy SideMedium High risk

to build & keep

building

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In summary: don’t use “internal” criteria

4

Make a balanced decision

The BI bar has been raised

It will take longer & cost more than you expected

You can’t let up on the pace for your strategy

What are you skipping in order to build?3

5

2

1

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Get the e-book at birst.com

©2015 Birst, Inc BEYOND THE TECHNICAL The complete guide to designing, pricing, & launching embedded analytic products

BEYOND THE TECHNICALThe complete guide to designing, pricing, & launching embedded analytic products

©2015 Birst, Inc BEYOND THE TECHNICAL The complete guide to designing, pricing, & launching embedded analytic products

BEYOND THE TECHNICALThe complete guide to designing, pricing, & launching embedded analytic products

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Thank you!ksmith@birst.com @kevinmsmith kevinmichaelsmith