Clio Cloud Conference 2015 - Entrepreneurship in Law: Applied Lessons from Modern Data Operations...

Entrepreneurship in Law:Applied Lessons from Modern data operations for your legal practice

By F rase r Newton & George Ps iha r i s

@Frase r_Newton @GeorgePs iha r i s

CLIO CLOUDC O N F E R E N C E

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George PsiharisVice President of Business Development at Clio

Fraser NewtonLead Scientist at Clio

a bit about us


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ME FIRST…Vice President of Business Development and with the Clio team since 2010.

• Have worked with Clio partners including bar associations, law schools, and

certified consultants;

• Currently work with the our Dublin-based team to introduce Clio to new markets,

starting with the UK;

• Most recently, have helped launch a new team at Clio focused on data operations.

• Along the way, I’ve always been tasked with launching, measuring, and building

new parts of the business at Clio.


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Lead Scientist and with the Clio team since 2008.

• Has worked as a Senior Software Developer and built many of the outstanding

product features you can experience in Clio today;

• Further worked as Clio’s Product Scientist, focusing on guiding product decisions

through data on customer experience and adoption;

• Extensive background in computer science and statistics;

• Now Clio’s Lead Scientist, was also a founding member of the new Data

Operations team at Clio.

…AND NOW FRASER

our agenda


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I. Understanding Data Operations as a new type of

business function;

II. How it works;

III. Applying these methods to your legal practice.


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your law firm is a service company that just happens to sell legal advice‟

how does that sound?

I. understanding data operations


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how do we use our resources to their best effect

to provide an excellent product, customer

experience, and 10x our revenue?

Product Customer ServiceMarketing, Business Development, Sales


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‟ Your goal shouldn't be to buy players, your goal should be to buy wins. And in order to buy wins, you

need to buy runs.


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Spooling up Data Operations

Data Inputs Analysis InsightsAction Plans +

Implementation


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Analysis

II. how does it work?


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• Take data and describe it in a way that can build deeper understanding of a

system;

• Every system is like a machine with inputs and outputs - analysis helps

understand and improve the efficiency and power of the machine.

• It does not have to be sophisticated; in fact, the fundamentals are the most

important part.

• One simple rule dominates: garbage in = garbage out.

WHAT IS ANALYSIS?


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START WITH #COUNTING


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• Successfully analysis does not require a Master’s Degree in Statistics;

• We’re not always doing deep-dives into bell curves and t-tests;

• Many of the most powerful ways to understand your business are simple

#counting and description techniques.

• Trust me, you can do this :)

WORKING WITH DATA


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• Paints a picture of the data;

• Can be counts, numerical summaries like sums, medians, and mean;

• Can also be visual representations like histograms, dot plots, line graphs,

scatter plots, or pie charts.

DESCRIPTION


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• Paints a picture of the data;

• Can be counts, numerical summaries like sums, medians, and mean;

• Can also be visual representations like histograms, dot plots, line graphs,

scatter plots, or pie charts.

DESCRIPTION


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INFERENCE• Inference is the process of taking data and saying something is true about

the system in general;

• Inference is useful and powerful, but not a requirement for driving your

business with data;

• No formal training in statistics is required - all you need is:

• The right mindset and curiousity driving you to understand your business;

• When in doubt, focus on #counting.


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DESCRIPTION VS. INFERENCE


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DESCRIPTION VS. INFERENCE


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DATA INSIGHTS• Analysis is not a goal in itself; the next step is to derive data insights;

• A data insight is a deeper understanding of a system based on data and analysis.

• Analysis is the evidence and data insight is the argument.

• Data insight connects data with meaning - it makes the data real and can reveal

something surprising about your business.

• Often, data insights confirm what you already know, but they are most useful

when they are surprising.


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DATA INSIGHTS - EXAMPLE• Analysis: 25% of your new revenue comes from referrals from existing

clients.

• Data insight #1: you have no referral program and make no attempt to

encourage happy clients to refer new clients.

• Data insight #2: launching a referral initiative is a potential source of new

growth.


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RECOMMENDATIONS• Recommendations turn data insights into action plans;

• Use new deeper understanding of your business to iterate, improve, and

drive change;

• It may be a true experiment or it may be as simple as a proof of concept

pilot project;

• Form a hypothesis that can be validated through testing.


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RECOMMENDATION - EXAMPLE• Recommend implementing a referral program on the hypothesis that referred

business is high quality and reliable, and that the program will increase the number

of referred clients.

• Low risk, not internally disruptive;

• Analysis and data insights should be proportional to the disruption and risk the

recommendation entails.

• Recommendations require an iterative process of counting, analyzing and providing

new data insights in order to determine if they are baseless or the case is made.


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IMPLEMENTATION• This realizes the action plan at both mechanical and organizational levels;

• This can require changing behaviours of people in the business;

• Recommendation must be accepted by leadership and embraced by the people involved as

the right thing to do.

• Must also lay the future foundation for future iterations.

• Example:

• We implement the referral program;

• Implementation must support counting the new referrals and whether they came through

‘organically’ or specifically through the program;

• Must also provide guidelines for success and reflection / review.

a case study from Clio:inbound sales team


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INBOUND SALES AT CLIO

Marketing leads Sales opportunities New customers


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STEP 1: #COUNTINGKey Performance Indicators (what)

• # of leads consumed (input)

• # of opportunities (output)

• # of paid customers (output)

• Revenue contributed to

business (output).


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STEP 1: #COUNTINGKey Performance Indicators (what)

• # of leads consumed (input)

• # of opportunities (output)

• # of paid customers (output)

• Revenue contributed to

business (output).

Operational Metrics (how)

• time to first contact;

• type of contact (phone/email)

• what % are contacted by day

1, week 1, etc.

• # of contact attempts made


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STEP 2: ANALYSISSome leads perform way better than others

Our best leads become opportunities quickly or not at all

We weren’t getting to our best leads fast enough

Contact time, method, and message varied by inbound sales rep


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STEP 3: DATA INSIGHTS• This analysis led us to two key data insights that we took to the business:

1. The team was at capacity and could not work all leads. There is an

opportunity to optimize, and focus capacity on our best performing

leads.

2. The individual members of the team did not follow the same process in

contacting and qualifying a lead. Adding more capacity might not deliver

a predictable result or proportionally increase performance.


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STEP 4: RECOMMENDATIONS

Implement lead prioritization - best leads first

Implement a standard operating procedure with SLAs

Introduce “service-level agreements” or SLAs


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STEP 5: IMPLEMENTATION• Get support and buy-in from leadership and the team itself;

• Extensive training for the inbound sales team on the new SOP;

• Implement new technology tools to support new workflows and SLAs;

• Launch and measure new operational metrics;

• Create a new role dedicated to managing and coaching the team on

following SOP, meeting SLAs;

• Monitor KPIs - these measure if the SOP is actually improving our business.


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STEP 6: RESULTS - # OF CALLS

Apr May June July Aug


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STEP 6: RESULTS - # OF OPPORTUNITIES

III. relating these lessons to your practice.


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your law firm is a service company that just happens to sell legal advice‟


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‟ Your goal shouldn't be to buy players*, your goal should be to buy wins. And in order to buy wins, you

need to buy runs.

*For law firms, insert “rainmakers” for “players”…


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YOUR LAW FIRM AS A SYSTEM

Client inquiries New matters Practice operations


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Client inquiries New matters

WHAT CAN A LAW FIRM COUNT?

• Total marketing / business development spend;

• # of new inquiries by channel;

• Conversion rate of inquiries to new business / matters;

• # of consultations to prospective new clients;

• Average response time to new inquiries;

• Cost of new client acquisition by channel.


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WHAT CAN A LAW FIRM COUNT?

• # of matters by attorney, by client, by practice area;

• Realization rates - utilization, billing, collections, etc.

• For litigators, total cases vs. cases won;

• Revenue/matters by fee structure - hourly, flat fee, contingency, etc.

• Gross, contribution, and profit margins;

• Client satisfaction levels.

New Matters Practice Operations


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EXAMPLE: COST OF ACQUISITION• #Counting: advertising spend by channel, # of new inquiries by channel; #

of consultations by channel, new clients by channel.

• Analysis: cost per new client was lowest for print media and referrals from

satisfied clients;

• Data insight: you spend way more on SEM than you do on print, and you

don’t measure your level of client satisfaction;

• Recommendation: test diverting some ad spend from SEM to print;

launch a Net Promoter Score survey to identify happy clients.


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EXAMPLE: IMPLEMENTATION• #Counting: how do I count / measure my advertising spend per channel

and attribute new client inquiries to these channels?


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Landing Page

Leads Clients

Revenue ROI Analysis

Phone Number

Social Media

AdWords

Article


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Source: https://www.netpromoter.com/know/

EXAMPLE: NET PROMOTER SCORE


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EXAMPLE: NET PROMOTER SCORE• #Counting: newly implemented survey collects NPS for current clients;

• Analysis: NPS is highest for the people you cite an effortless experience getting updates on

their legal matters;

• Data insight: investing in easy client communication early increases NPS score and potential

referrers of affordable new business;

• Recommendation: launch a new standard operating procedure for client communication and

introduce an SLA - e.g. once per week minimum with set reminders. Offer online client portals

with access to matter updates.

• Implementation: Some clients get annoyed, remove them from SOP. Some clients don’t like

to use online portals - offer alternatives.


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Thank You.

IV. appendix - useful resources


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APPENDIX - USEFUL RESOURCES• Entrepreneurship in law: KPI Presentation from 2014;

• More information on Net Promoter Score: https://www.netpromoter.com/know/;

• Moneyball. http://www.amazon.com/Moneyball-The-Winning-Unfair-Game/dp/

0393324818;

• Edward Tufte, The Visual Display of Quantitative Information http://

www.edwardtufte.com/tufte/books_vdqi.

• DJ Patil & Hilary Mason, Data Driven: Creating a Data Culture http://www.oreilly.com/

data/free/data-driven.csp.

Date post:	10-Feb-2017
Category:	Law
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