SMB Nation Blog

SMB Nation has been serving the Bainbridge Island area since 2001, providing IT Support such as technical helpdesk support, computer support, and consulting to small and medium-sized businesses.

3 Things Are Holding Back Your Analytics, and Technology Isn’t One of Them

 by Todd Clark and Dan Wiesenfeld

M and M

During the past decade, business analytics platforms have evolved from supporting IT and finance functions to enabling business users across the enterprise. But many firms find themselves struggling to take advantage of its promise. We’ve found three main obstacles to realizing analytics’ full value, and all of them are related to people, not technology: the organization’s structure, culture, and approach to problem solving.


Structurally, analytics departments can range between two opposite but equally challenging extremes. On the one hand are data science groups that are too independent of the business. These tend to produce impressive and complex models that prove few actionable insights.

Consider the experience of one retail financial services firm. There, the analytics function was comprised of employees who used specialized software packages exclusively and specified complicated functional forms whenever possible. At the same time, the group eschewed traditional business norms such as checking in with clients, presenting results graphically, explaining analytic results in the context of the business, and connecting complex findings to conventional wisdom. The result was an isolated department that business partners viewed as unresponsive, unreliable, and not to be trusted with critical initiatives.

On the other hand, analysts who are too deeply embedded in business functions tend to be biased toward the status quo or leadership’s thinking. At a leading rental car agency, for instance, we watched fleet team analysts present intelligence purportedly showing that the fleet should skew toward newer cars. Lower maintenance costs more than compensated for the higher depreciation costs, they said. This aligned with the fleet vice president’s preference for a younger fleet.

But it turned out that the analysts had selected a biased sample of older cars with higher-than-average maintenance costs among cars of the same age. An analysis of an unbiased sample (or the entire population) would have yielded a different result. (Of course there might have been other motivations to keep a younger fleet—customer satisfaction and brand perception, to name two—but cost reduction was not one of them.)


Culturally, organizations that are too data-driven (yes, they exist) will blindly follow the implications of flawed models even if they defy common sense or run counter to business goals. That’s what happened at a financial services firm where management was mulling a change to its commission structure. They wanted to switch the basis of its salesforce compensation from raw results to performance relative to the potential of each salesperson’s market.

In response, analysts developed an admirable data envelopment model. The model simultaneously compared sales of different types of products with local demographic and financial statistics to come up with a single efficiency measure for each salesperson relative to their peers. Indeed, this seemed to have made compensation more equitable. But it reduced the compensation of salespeople who were less efficient but ultimately more valuable—causing them to defect to competitors.

Alternatively, organizations that rely too heavily on gut instinct resist adjusting their assumptions even when the data clearly indicates that those assumptions are wrong. The aforementioned rental car agency, for example, was extremely reluctant to change course even after discovering that the data didn’t support their cost reduction claims.

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Harry’s New Side Hustle in Analytics

Pre-recession, my basic mo·dus op·e·ran·di (MO) was to take fun seriously in business. I’ve emerged battle-tested over the past decade and have adopted a tougher stance on life: Lead…or follow…or get out of the way. I still try to have fun where I can find it but the economy isn’t as fun as a decade ago and neither am I!

First, before you proceed, I’d ask you to peruse my LinkedIn profile HERE so you  bigdatacan get the foundation to understand the context I’m about to present. Hopefully you’ll note that I’m committed to education both formal and semi-formal (that would be my technology-related certifications). Second, my goal is to lead by example and have your follow along and join the parade. Third, as I’ve opined many times over the past few years. Small Business Server is GONE and it’s time to reinvent ourselves. You’ve done it before; you can do it again.

Side Hustle
It’s all Karl Palachuck’s fault. About 20-months ago at the Microsoft Worldwide Partner Conference (2016), it announced a “degree” in Data Science. Karl signed up to participate in this and I openly questioned whether it could be called a “degree” as Microsoft is not an accredited University. Fast forward the movie and the program has been rebranded a professional certificate (which is appropriate) and the title is Microsoft Professional Program. There are three majors: Data Science, Big Data and DevOps. Note that these are “earned” certificates; not honorary. These are the real deal.

I’m pursuing the Big Data certificate for a few reasons. It’s how I’m wired (I’m not a developer and flunked out of C++ years ago). I was a SQL Server MCSE in the late ‘90s to support my employer (Clark Nuber) and its vaunted Microsoft Great Plains Dynamics accounting consultant practice (once Great Plains Dynamics abandoned Btrieve on the NetWare platform, it adopted SQL Server as the engine on a Windows NT Server network). The Big Data certificate is a natural extension of my background in this area. Finally, many readers know I recently exited a Seattle-based Big Data startup in Predictive Analytics and I want to go all in and double down in this area as the New Harry!

Program Referrals

You’d be amazed concerning the support I have received when I have made mention of my latest education side hustle. After a brief mention in one of the recent MSP Tech Talk lectures (you can sign up HERE for Spring quarter where one of the lectures is a deeper dive on marketing analytics), I received several inquiries about the program and the sign-up link. Ditto a catch-up coffee last Friday with Brandon from Bainbridge Technology and his wife (she has a data analyst background). Finally, there was my friend who works for a State of California’s I-Bank (Infrastructure and Economic Development Bank) and is seeking to take his career to the next level with his passion concerning alternative energy such as solar power (yes – Big Data plays nicely in science to).

Just ‘Da Facts
I know. I know. Get to the fricking point Harry!

In the Microsoft Professional Program Big Data certification HERE – there are ten required courses that take 12-30 hours each to complete. The education outcome is to train you in eight new skills. Each course runs for three months and starts at the beginning of a quarter. January—March, April—June, July—September, and October —December. The capstone runs for four weeks at the beginning of each quarter: January, April, July, October. Accordingly, I have budgeted two years to complete this journey. Not only do I want to acquire new skills along the way but I want to demonstrate forward professional progress. Again, I implore you to join me right here right now.

Last missive. This is essentially free for Microsoft Partners. I consider this to be in the neighborhood of a several thousand-dollar subsidy compared to what you might pay for other programs. You can pay $99 USD to receive a completion certificate suitable for framing – something I’ll treat myself to upon successful completion.

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Dana Epp's New Main Hustle!


This is a "Where is he now? Dana Epp’s new startup!" startup piece. Read on.

Few SMB Nation event speakers captivated like Dana Epp at our Fall Conferences. In SMB Nation 2009, Epp spoke in a packed, long narrow room at the now demolished Riviera Hotel in Las Vegas. He performed live hacking before a mesmerized audience (long before Kevin Mitnick started his current road show). Fast forward

the movie and Dana enjoyed well-deserved success directing his last security focused startup (Scorpion Software) to an ultimate full acquisition by Kaseya, danaeppan investor-backed RMM ISV.

Disappearing Act
With all due respect, post-acquisition Epp and SMB Nation lost touch. As is often the case, the acquirer asks or requires the acquired party to join the parent company for a period of time to assist in the logistics such as brand transition. That’s exactly what Epp did – joining Kaseya as one of their principal architects. A year later Dana was promoted to CTO and asked to redefine software engineering at Kaseya. With Epp’s focus on his day job, we missed our occasional conversations.

New Startup: Wildrook
Recently my LinkedIn notification made mention of Dana’s professional update. I double-clicked down and discovered that Dana had exited Kaseya and was out in the wild again, starting Wildrook in his hometown of Vancouver BC. I spoke at length with Epp to get the scoop. Epp’s tenure at Kaseya arrived at a completion milestone once he integrated Scorpion Software into its operations and he helped fundamentally transform the CTO role. The call of the wild to get back into the startup scene resulted in the formation of Wildrook ( The core solution, called AuditWolf, is the cloud threat protection platform to protect your cloud resources in Azure. The topic of a whole ‘nother future blog post, AuditWolf takes advantage of Microsoft’s Cloud Management APIs to start aggregating data related to configuration changes, host setup and activity and user interactions with resources in Azure ,all without impacting live services. It then applies Dana’s expertise and experience in Azure security (he’s been a Microsoft Security MVP for 14 years now) to make sure your data and deployments are properly secured. “We allow you to gain operational intelligence and insight into the security of your data and deployments hosted in the cloud.” Epp shared.

When asked “why” he was building his new startup, Epp responded by saying “it is far too easy for IT professionals to screw up security in Azure. I see it every day. With the proliferation of public cloud computing outpacing cybersecurity defenses, and the concepts or IT administration blurring with DevOps to drive “Infrastructure as Code (IaC), a single click or command in the Azure Portal can cause a security violation if you don’t know the impact of that decision. And you won’t even know you did it... until it’s too late. That’s a real pain point. We can solve it.”

“At the highest level, we help you get the big picture with a contextual view of your Azure environment, and constantly monitor for change. Our report card paradigm and grading system allows you to see how we rank your cloud risks and helps to prioritize remediation efforts.” Epp said. “Then AuditWolf helps you remediate your risk by by generating the commands to run in Azure to fix the security violation(s), educating your administrators responsible for managing the cloud infrastructure while helping them fix it.”

Hear from Epp
Epp will led a security lecture in our MSP Tech Talk – Spring Quarter in late June. You can click HERE to sign-up for this complimentary speech. And there you have it. Epp is alive and kicking across the border in Canada. Yes – he’s back, helping to keep us secure!

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3 Data Science Methods and 10 Algorithms for Big Data Experts

Data Science

One of the hottest questions in Information Management now is how to deal with Big Data in all its applications: how to gather, store, secure, and – possibly most importantly – interpret what we collect. Organizations that are able to apply effective data analysis to massive amounts of data gain significant competitive advantages in their industries.

Organizations no longer question the value of gathering and storing such data but are far more heavily focused on methods to make sense of that all the valuable information that data represents. Although security and storage remain critical issues for IT departments, organizations are finding that their commitment to Big Data can’t stop there – they must be able to make sense of their data, to know what data is valid, relevant, and usable, as well as how to use it.

The more data an organization has, the more difficult it is to process, store, and analyze, but conversely, the more data the organization has, the more accurate its predictions can be. As well big data comes with big responsibility. Big data requires military-grade encryption keys to keep information safe and confidential.

This is where data science comes in. Many organizations, faced with the problem of being able to measure, filter, and analyze data, are turning to data science for solutions – hiring data scientists, people who are specialists in making sense out of a huge amount of data. Generally, this means making use of statistical models to create algorithms to sort, classify, and process data.

What is Data Science?

Data science has been a term in the computing field since around 1960 when it was first floated as a substitute for the term “computer science”. Over the next twenty years or so, it gradually came to mean that blend of statistics and methodology that specifically pertained to data analysis. However, it was not until the much more recent emergence of Big Data and its role in organizational development and direction, that data science began to be a fundamental requirement of any organization working out how to analyze such massive amounts of data.

Data science is interdisciplinary, incorporating elements of statistics, data mining, and predictive analysis, and focusing on processes and systems that extract knowledge and insights from data. It is also known as “analytics transformation” because the goal is to “transform” raw data into usable insights. It has also been called “industrial analytics” because the context is industrial rather than scientific – to analyze data for competitive or quality improvements that can be gained by having a better understanding of one’s customers, potential customers, service model, and almost any aspect of the organization that can be represented in bytes.

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RapidFire Tools, Inc. Launches “Audit Guru,” The First Tool to Automate and Streamline GDPR Compliance Audits

New Software Appliance and Portal is Purpose-built for MSPs to Help Their Clients Navigate the Complex General Data Protection Regulation Mandates.

ATLANTA, GA, USA –March 5, 2018– RapidFire Tools Inc. today announced the availability of Audit Guru for GDPR™, the world’s first compliance process automation solution designed to address the sweeping new EU General Data Protection Regulation (GDPR), which becomes law on the May 25, 2018. The tool is being offered exclusively through the RapidFire Tools RapidFirechannel of authorized Audit Guru partners, and includes a robust cloud-based portal that resellers can use to manage the entire GDPR audit and reporting process. MSPs can provide an array of value-added GDPR services built around Audit Guru, which can range from a simple and straight-forward resale of the tool to organizations that have their own internal IT and compliance staff, all the way up to a fully managed, ongoing GDPR Compliance-as-a-Service offering.

“The new GDPR requirements put into place tough new standards that regulate how personal information is collected, electronically stored, and secured,” noted Rapidfire Tools CEO, Mike Mittel. “These new laws impact every company that collects data about any individual living in the European Union. There is a huge amount of confusion, fear and uncertainty associated with GDPR because of the fines and crippling sanctions associated with non-compliance,” he added. “Audit Guru addresses these concerns by providing MSPs with a solution that literally guides them through the compliance process, automates the collection of necessary data, and generates the required documents.”

The new offering leverages the same technology found in Network Detective, the company’s market-proven, award-winning family of IT assessment, documentation and reporting tools. “This is not just another check-list product with a laundry list of tasks that the MSP has to perform,” explained Win Pham, lead developer of the tool. “We've created a turn-key virtual software appliance that automates the production of mandatory compliance reports, provides ongoing issues detection, and manages the manual collection of supplemental information required from key stakeholders.”

The marketing opportunity extends far beyond MSPs located within the European union. “As if the EU isn’t a big enough market, even if the MSPs or their clients are based outside of the EU, if they own electronic database files that contain personal information about customers, prospects and other individuals who are based inside the EU, they are subject to the regulation,” explained Mark Winter, RapidFire Tools’ vice president of sales. “This makes the market for Audit Guru even broader for MSPs, MSSPs, and VARs who wish to expand their offerings to include GDPR compliance services.”

Audit Guru is sold to MSPs directly by RapidFire Tools or through any of their European distributors. MSPs who are interested in becoming an Audit Guru Reseller Partner should visit, send an email to This email address is being protected from spambots. You need JavaScript enabled to view it., or call +1-678-323-1300, ext. 2.


About RapidFire Tools
RapidFire Tools, Inc is the leading global supplier of business-building technology tools for MSPs to help them close more business, offer more services, keep more customers, and make more money. The company’s offerings include: a complete set of IT Assessment, Documentation and Reporting tools; tools for IT Compliance Process Automation; and tools for Insider Cyber Threat Detection & Alerting.
European distributors include: Achab (Italy), Prianto (UK), and Upstream (Denmark, Iceland, Finland, Norway, Sweden).


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