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Ziff Davis | White Paper | Analytics For Everyone - Even You
Introduction
Our ability to collect and analyze data and then make decisions based on powerful insights has
exploded in recent years – if you have the tools and skills to unlock the information within vast
data stores. For too many of us, this means cobbling together data in a spreadsheet or asking
IT to build reports and dashboards. Even then, data is often overwhelming and deriving real
insights from spreadsheets is challenging at best (and impossible at worst).
Yet, we are all hungry for data and information. The desire to be “data-driven” isn’t limited to the
C-suite. There needs to be a better way for everyone to not just access data but interact with it
and then take action.
What Gets In the Way of Analytics For Everyone?
Ziff Davis recently surveyed 450 business people like you about their current use of analytics
and the challenges they face incorporating analytics into regular decision-making. Not
surprisingly, access to data and the ability to analyze data without help from IT or a business
analyst topped the list of barriers to more frequent use of analytics. Over 62% of respondents
noted that either the complexity of tools or the need to go through other staff and departments
got in the way of meaningfully applying analytics to decision making.
What Are We Trying To Analyze?
There are vast amounts of transactional data sitting in a variety of business systems that aren’t
being leveraged. CRM, ECM, SCM, web analytics, ERP and more can all be used to guide both
daily and strategic decisions. Most of us however, can rarely get at the raw data, relying instead
0% 5% 10% 15% 20% 25% 30% 35% 40% 45%
Other
Math skills to do analysis
None. We're a data-driven organization
Expense
Wait time. My organization doesn't have analytics tools I can
use without going through IT/business analyst
Access to an analytics tool that is simple for me to use
Access to the data to do analysis
What are your biggest barriers to using analytics more frequently to
inform decision making?
% Respondants
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Ziff Davis | White Paper | Analytics For Everyone - Even You
on reports and dashboards. Even if we can dig deeper than routine reporting might allow, we’re
still facing an uphill battle. Aggregating the data and then finding relationships between sales
data from a CRM system and training data from HR, for example, is rarely something that can
happen without input from a dedicated analyst or data manager in IT.
This gets at the very nature of ad hoc analysis that most of us attempt every day. The Ziff Davis
survey noted above found that nearly 60% of respondents used analytics daily or weekly to
make decisions, but the overwhelming majority (70%) used spreadsheets for the task. Often,
there is no choice but to pull data manually from reports or dashboards into a spreadsheet,
combining it with their own data to derive insights relevant to their specific jobs.
We are also beginning to make use of publicly available datasets, ranging from climatic data
to information from public transit systems. These types of data rarely make it into standard
business intelligence systems, leaving the arduous task of preparing corporate, public, and
personal data for analysis. If an accountant has a hypothesis about the relationship between
flu outbreaks and sales performance, how can they reliably test their theories and take action
to correct sales forecasts based on the data? These are fairly sophisticated analyses in and
of themselves, but they represent the sorts of explorations that most of us would happily
undertake if we had the right tools
What Do You Want Out Of An Analytics Solution?
The Ziff Davis survey identified a wide spectrum of analytics needs. Respondents called
out sales processes, insight into marketing campaigns, and customer churn as top areas
they wanted to improve with analytics, but their interests were as varied as their jobs. This is
consistent with anecdotal evidence, but the bottom line is that we all want to be part of what
Gartner calls “analytic organizations”1
rather than just businesses that use analytics.
0% 5% 10% 15% 20% 25% 30% 35% 40% 45%
Other
Anticipate equipment maintenance
Improve employee recruitment and retention
Reduce customer churn
Gain insight into marketing campaigns
Improve logistics
Anticipate product demand
Evaluate employee performance
Assess financial risk
Improve customer targeting and personalization
Improve sales processes
Improve IT processes and procurement
Improve quality control
What do you want to accomplish in your organization with analytics?
% Respondants
1. http://www.gartner.com/newsroom/id/2985317
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Consumers use a wide variety of data
regularly to make decisions. Customer
ratings and reviews, opinions from social
networks, news, trends, etc., all influence
buying decisions. Now these consumers
are coming to work and expecting to
have that same broad access to data to
make work decisions. And why shouldn’t
they? Business conditions change too
rapidly to wait for a report author in IT to
assemble a dashboard with key metrics. More significantly, many of us are looking far beyond
a regurgitation of historical data, and. are rightfully demanding tools that let us move beyond
gut feelings and hunches.
Focus On Insights, Not the Complexities of Data Management and
Analytics
Deriving insights from an organization’s data is a circuitous process involving multiple tools and
people. Getting IT to build the correct views and prepare data for analysis, asking business
analysts to code reports, and finding someone to help interpret results takes more time
and effort than the average person can spare. But most of us aren’t in a position to write
specifications or describe their requirements in ways that IT can quickly translate into usable
information.
The chart below, reflecting data from the Ziff Davis survey, echoes the need for an analytics
platform that is easy to use, integrates simply with other information systems, and promotes
collaboration.
Analytics can help drive business
forward, but it’s up to the individual
to use the available data to create
new business opportunities. Putting
data in the hands of all employees
allows innovation to occur.
-Gartner, 2015
0% 10% 20% 30% 40% 50% 60% 70% 80%
Other
Limited exposure to underlying math and computing
Cloud-based for simple deployment and ubiquitous access
Ability to interact with others on analyses to quickly come to
consensus
The ability to ask plain language questions and get visual
answers
Wizards and tools to recommend analytic approaches
Sharing insights with others to drive more meaningful
discussions
Simple integration with existing data stores
Ease of use
What capabilities and features would allow you to use analytics more
broadly in decision making?
% Respondants
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How then, can we cut out the middlemen and put insights directly into the hands of those
who need them the most? And not just when IT has the resources to get the job done, but
right now? You need to be able to easily tell a story visually and predict the impact of everyday
decisions without help from IT and regardless of your own analytical proficiency. What if a
single solution could deliver all of this via the web to you in ways that make sense intuitively
and let you take action?
Eliminate the Obstacle of Data Preparation
People across organizations ask great questions. Can we do a better job predicting delays in
deliveries for certain raw materials? Why do so many support calls about a particular product
get escalated? Why do our local ad campaigns do better in some regions than in others?
These are all reasonable questions but pulling together the right data to answer them can be
onerous for data scientists and impossible for the rest of us. The data may need to come from
systems that were never designed to be integrated or might involve individually maintained
spreadsheets as well as records from enterprise information systems. Data quality can be
hard to assess and most users aren’t equipped to reliable join and merge tables from multiple
sources.
Even for dedicated analysts and data scientists, the ability to rapidly explore data, slicing and
dicing with a few clicks instead of complicated queries can be a powerful accelerator. No
matter who is accessing the data, preparing it for analysis and drawing the right information
from the right sources is a frequent and substantial barrier to delivering insights.
Addressing the Skills Gap
Almost 70% of the respondents to the Ziff Davis survey noted previously described their
analytics skills as either beginner or intermediate.
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
50%
Beginner Intermediate Advanced Master
How do you rate your analytics skills?
% Respondants
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Even assuming that they have access to clean, reliable data, the lack of specific analytics
skills makes basic exploratory analysis difficult. Exploratory analysis is fundamental to more
sophisticated analytics. Without it, you can’t know what you don’t know.
Taking the next step to predictive analytics is an even bigger lift. There is a reason that
predictive modeling has largely been the domain of statisticians and data scientists over the
years. It is both programmatically and mathematically complicated and the necessary skills
aren’t easily imparted with a few training sessions. Data scientists are in short supply, though
(and often don’t even exist outside of larger organizations); others in the organization have
increasingly sophisticated analytics needs even if their analytical skill doesn’t match their
expertise in their line of business. Frankly, it shouldn’t have to. The right solutions would allow
everyone to use data to think ahead about business problems without knowing they are
engaging in predictive analytics.
Let the Cloud Do the Heavy Lifting
Powerful analytics solutions have traditionally been both complicated and expensive to deploy.
Whether implemented as desktop solutions or centralized in the data center, it is difficult to
justify making analytics tools widely available when the software and infrastructure to make
it work require considerable investments. As it has with so many other elements of modern
business, though, cloud computing has the power to bring incredible processing power and
storage capacity directly to users through their web browsers.
The cloud doesn’t just reduce costs or deployment complexities. It makes analytics available
anytime, anywhere. Direct sales forces can access analytics on the road, improving customer
targeting and directing their efforts at the deals that are most likely to close. Distributed and
remote workers can have the same experience as their colleagues in the home office. Field
maintenance staff can predict where problems will occur and proactively fix equipment instead
of reacting to failures.
This also means that smaller organizations can begin to leverage analytics just like their larger
peers without significant capital expenditures. Analytics shouldn’t just be for users in large
enterprises; all organizations should be able to make better decisions with data.
Don’t Keep the Insights To Yourself
Most of us operate differently than data scientists
or business analysts – we are already working
in teams or are deeply vested in particular
departments instead of working across
departments or at more strategic levels in our
organizations. The ability to share and collaborate
around insights is critical for individuals and our
colleagues.
42% of business users want to
be able to interact with others
on analyses to quickly come to
consensus. 45% want to share
insights with others to drive
more meaningful discussions.
-Ziff Davis End User Analytics Survey
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Part of this is enabled by visual storytelling. In other cases, the solution itself needs to support
collaborative approaches to analytics. In either scenario, if insights can’t be made available
to others inside and outside a specific line of business, then the analytics solution has much
lower value to the organization as a whole and will be less likely to create meaningful change
and innovation.
A Closer Look At Watson Analytics
Throughout this paper, we have explored important capabilities and use cases for modern
approaches to analytics. “Everyday analytics,” in which the use of data to make decisions
pervades an organization and reaches everyone, is a powerful idea whose time has come.
Even though the demand for solutions that ticked off all of the boxes we’ve discussed has
been very high, the technology simply hasn’t been available to make it all happen until now.
Watson Analytics from IBM puts advanced capabilities directly into hands of everyone. It
removes challenges of mathematical modeling and data preparation. As its name suggests,
Watson Analytics is a cognitive platform that provides with multiple entry points to data and
analytics projects. People will potentially approach analytics from a wide variety of learning
styles, business perspectives and analytical expertise; Watson Analytics can accommodate all
of them.
When You Already Know What You Want
If you already know what data you want to explore, Watson Analytics allows you to upload your
own data, connect to existing data sources and build dashboards on the fly. It automatically
assesses the quality of your data and attempts to improve data quality wherever possible. From
there, you can drill down deeper into the data and move on to more advanced analytics.
When You Have a Hunch
If you have a hypothesis to test or a hunch to investigate, you can ask Watson Analytics a
question in plain English. An IT administrator, for example, could ask which types of helpdesk
tickets take the longest to resolve while an operations staffer could ask about factors that are
likely to cause product failures.
When You Don’t Know Where to Start
Because even exploratory data analysis can be overwhelming, Watson Analytics automatically
look across data and suggests the most interesting starting points. Watson can detect
“Cognitive analytics offers a way to bridge the gap between big data
and the reality of practical decision making.”
-Deloitte University Tech Trends 2014
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relationships and trends, automatically formulating potential interesting analyses or offering
helpful reports, all in plain language.
Conclusion
Making data available to broad groups isn’t especially challenging for IT departments with
the desire and wherewithal. Business intelligence tools have been generating reports and
dashboards and even allowing a degree of self service for some time. However, actually
delivering insights to everyone when and where they need them is far more difficult. Data
preparation, differing levels of analytic expertise, and complicated analytics tools have all
stood in the way of users who simply need good data and intuitive platforms to let data inform
practical, everyday decisions.
Watson Analytics provides a complete, easy to use platform for everything from exploratory
analysis to sophisticated predictive analytics, all without the need for complicated mathematics
or statistical programming. Because it’s delivered via the cloud, new features will be rolled out
regularly and users from organizations of all sizes can begin taking advantage of this powerful
platform right now.
To learn more about Watson Analytics from IBM, go to www.watsonanalytics.com
