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Month: July 2016

Hadoop is Now a General-purpose Platform

As seen in SD Times

HadoopApache Hadoop adoption is accelerating among enterprises and advanced computing environments as the project, related projects, and ecosystem continue to expand. While there were valid reasons to avoid the 1.x versions, skeptics are reconsidering since Hadoop 2 (particularly the latest 2.2.0 version) provides a viable choice for a wider range of users and uses.

“The Hadoop 1.x generation was not easy to deploy or easy to manage,” said Juergen Urbanski, former chief technologist of T-Systems, the IT consulting division of Deutsche Telecom. “The many moving parts that make up a Hadoop cluster were difficult for users to configure. Fortunately, Hadoop 2 fills in many of the gaps. Manageability is a key expectation, particularly for the more critical business use cases.”

Hadoop 2.2.0 adds the YARN resource-management framework to the core set of Hadoop modules, which include the Hadoop Common set of utilities, the Hadoop Distributed File System (HDFS), and Hadoop MapReduce for parallel processing. Other improvements include enhancements to HDFS, binary compatibility for Map/Reduce applications built on Hadoop 1.x, and support for running Hadoop on Windows.
Meanwhile, Hadoop-related projects and commercial products are proliferating along with the ecosystem. Collectively, the new Hadoop capabilities provide a more palatable and workable solution, not only for enterprise developers, business analysts and IT, but also a larger community of data scientists.

“There are many technologies that are helping Hadoop realize its potential as being a more general-purpose platform for computing,” said Doug Cutting, co-creator of Hadoop. “We started out as a batch processing system. People used it to do computations on large data sets that they couldn’t do before, and they could do it affordably. Now there’s an ever-increasing amount of data processing that organizations can do using this one platform.”

YARN expands the possibilities
The limitations of Map/Reduce were the genesis of Apache Hadoop NextGen MapReduce (a.k.a. YARN), according to Arun Murthy, release manager for Hadoop 2.

“It was apparent as early as 2008 that Map/Reduce was going to become a limiting factor because it’s just one algorithm,” he said. “If you’re trying to do things like machine learning and modeling, Map/Reduce is not the right algorithm to do it.”

Rather than replacing Map/Reduce altogether, it was supplemented with YARN to provide things like resource management and fault tolerance as base primitives in the platform, while allowing end users to do different things as they process and track the data in different ways.

“The architecture had to be more general-purpose than Map/Reduce,” said Murthy. “We kept the good parts of Map/Reduce, such as scale and simple APIs, but we had to allow other things to coexist on the same platform.”

The original Hadoop MapReduce was based on the Google Map/Reduce paper, while Hadoop HDFS was based on the Google File System paper. HDFS provides a mechanism to store huge amounts of heterogeneous data cheaply; Map/Reduce enables highly efficient parallel processing.

“Map/Reduce is a mature concept that comes from LISP and functional programming,” said Murthy. “Google scaled Map/Reduce out in a massive way while keeping a real simple interface for the end user so the end user does not have to deal with the nitty-gritty details of scheduling, resource management, fault tolerance, network partitions, and other crazy stuff. It allowed the end user to just deal with the business logic.”

Because YARN is an open framework, users are free to use algorithms other than Map/Reduce. In addition, applications can run on and integrate with it.

“The scientific and security computing communities depend on Open MPI technologies, which weren’t even an option in Hadoop 1,” said Edmon Begoli, CTO of analytics consulting firm PYA Analytics. “The architecture of Hadoop 2 and YARN allows you to plug in your own resource manager and your own parallel processing algorithms. People in the high-performance computing community have been talking about YARN enthusiastically for years.”

HDFS: Aspirin for other headaches
Some CIOs have been reluctant to bring Hadoop into the enterprise because there have been too many barriers to entry, although Hadoop 2 improvements are turning the tide.

“I think two of the deal breakers were NameNode federation and the Quorum Journal Manager, which is basically a failover for the HDFS NameNode,” said Jonathan Ellis, project chair for Apache Cassandra. “Historically, if your NameNode went down, you were basically screwed because you’d lose some amount of data.”

Hadoop 2 introduces the Quorum Journal Manager, where changes to the NameNodes are recorded to replicated machines to avoid data loss, he said. NameNode federation allows a pool of NameNodes to share responsibility for an HDFS cluster.

“NameNode federation is a bit of a hack because each NameNode still only knows about the file set it owns, so at the client level you have to somehow teach the client to look for some files on one NameNode and other files on another NameNode,” said Ellis.

HDFS is nevertheless an economically feasible way to store terabytes or even petabytes of data. Facebook has a single cluster that stores more than 100PB on Hadoop, according to Murthy.

“It’s amazing how much data you can store on Hadoop,” he said. “But you have to interact with the data, interrogate it, and come up with insights. That’s where YARN comes in. Now you have a general-purpose data operating system, and on top of it you can run applications like Apache Storm.”

John Haddad, senior director of product marketing at Informatica, said the Hadoop 2 improvements allow his organization to run more types of applications and workloads.

“Various teams can run a variety of different applications on the cluster concurrently,” he said. “Hadoop 1 lacked some of the security, high availability and flexibility necessary to have different applications, different types of workloads, and more than one organization or team submitting jobs to the cluster.”

Gearing up for prime time
The number and types of Hadoop open-source projects and commercial offerings are expanding rapidly. Hadoop-related projects include HBase, a highly scalable distributed database; the Hive data warehouse infrastructure; the Pig language and framework for parallel computing; and Ambari, which provisions, manages and monitors Apache Hadoop clusters.

“It seems like we’ve got 20 or 30 new projects every week,” said Cutting. “We have all these separate, independent projects that work together, so they’re interdependent but under separate control so the ecosystem can evolve.”

Meanwhile, solution providers are building products for or integrating their products with Hadoop. Collectively, Hadoop improvements, open-source projects and compatible commercial products are allowing organizations to tailor it to their needs, rather than having to shoehorn what they are doing into a limited set of capabilities. And the results are impressive.

For example, Oak Ridge National Laboratory used Hadoop to help the Center for Medicare and Medicaid Services identify tens of millions of dollars in overpayments and fraudulent transactions in just three weeks.

“Using only two or three engineers, we were able to approach and understand the data from different angles using Hive on Hadoop because it allowed us to write SQL-like queries and use a machine-learning library or run straight Map/Reduce queries,” said PYA Analytics’ Begoli. “In the traditional warehousing world, the same project would have taken months unless you had a very expensive data warehouse platform and very expensive technology consulting resources to help you.”

The groundswell of innovation is enabling Hadoop to move beyond its batch-processing roots to include real-time and near-real-time analytics.


The groundswell of innovation is enabling Hadoop to move beyond its batch-processing roots to include real-time and near-real-time analytics.

Skeptics are doing a double take
Hadoop 2 is converting more skeptics than Hadoop 1 because it’s more mature, it’s easier (but not necessarily easy) to implement, it has more options, and its community is robust.

“You can bring Hadoop into your organization and not worry about vendor lock-in or what happens if the provider disappears,” said Murthy. “We have contributions from about 2,000 people at this point.”

There are also significant competitive pressures at work. Organizations that have adopted Hadoop are improving the effectiveness of things like fraud detection, portfolio management, ad targeting, search, and customer behavior by combining structured and unstructured data from internal and external sources that commonly include social networks, mobile devices and sensors.

“We’re seeing organizations start off with basic things like data warehouse optimization, and then move on to other cool and interesting things that can drive more revenue from the company,” said Informatica’s Haddad.

For example, Yahoo has been deploying YARN in production for a year, and the throughput of the YARN clusters has more than doubled. According to Murthy, Yahoo’s 35,000-node cluster now processes 130 to 150 jobs per day versus 50 to 60 before YARN.

“When you’ve got 2x over 35,000 to 40,000 nodes, that’s phenomenal,” he said. “It’s a pretty compelling story to tell a CIO that if you just upgrade your software from Hadoop 1 to Hadoop 2, you’ll see 2x throughput improvements in your jobs.”

Of course, Hadoop 2.2.0 isn’t perfect. Nothing is. And some question what Hadoop will become as it continues to evolve.

Hadoop co-creator Cutting said the beauty of Hadoop as an open-source project is that new things can replace old things naturally. That prospect somewhat concerns PYA Analytics’ Begoli, however.

“I’m concerned about the explosion of frameworks because it happened with Java and it’s happening with JavaScript,” he said. “When everyone is contributing something, it can be too much or the original vision can be diluted. On the other hand, a lot of brilliant teams are contributing to Hadoop. There are management tools, SQL tools, third-party tools and a lot of other things that are being incubated to deliver advanced capabilities.”

While Hadoop’s full impact has yet to be realized, Hadoop 2 is a major step forward.

Well-known Hadoop implementations

Amazon Web Services: Amazon Elastic MapReduce uses Hadoop in order to provide a quick, easy and cost-effective way to distribute and process large amounts of data across a resizable cluster of Amazon EC2 instances. It can be used to analyze click-stream data, process vast amounts of genomic data and other large scientific data sets, and process logs generated by Web and mobile applications.


Six Ways to Master the Data-Driven Enterprise

As seen in InformationWeek.

StatisticsBig data is changing the way companies and industries operate. Although virtually all businesses acknowledge the trend, not all of them are equally prepared to meet the challenge. The companies in the best position to compete have transformed themselves into “data-driven” organizations.

Data-driven organizations routinely use data to inform strategy and decision-making. Although other businesses share the same goal, many of them are still struggling to build the necessary technological capabilities, or otherwise their culture is interfering with their ability to use data, or both.

Becoming a data-driven organization isn’t easy, however. In fact, it’s very difficult. While all organizations have a glut of data, their abilities to collect it, cleanse it, integrate it, manage it, access it, secure it, govern it, and analyze it vary significantly from company to company. Even though each of these factors helps ensure that data can be used with higher levels of confidence, it’s difficult for a business to realize the value of its data if its corporate culture lags behind its technological capabilities.

Data-driven organizations have extended the use of data across everyday business functions, from the C-suite to the front lines. Rather than hoping that executives, managers, and employees will use business intelligence (BI) and other analytical tools, companies that are serious about the use of data are training employees, making the systems easier to use, making it mandatory to use the systems, and monitoring the use of the systems. Because their ability to compete effectively depends on their ability to leverage data, such data-driven organizations make a point of aligning their values, goals, and strategies with their ability to execute.

On the following pages we reveal the six traits common to data-driven organizations that make them stand out from their competitors.

Forward Thinkers

Data-driven enterprises consider where they are, where they want to go, and how they want to get there. To ensure progress, they establish KPIs to monitor the success of business operations, departments, projects, employees, and initiatives. Quite often, these organizations have also established one or more cross-functional committees of decision-makers who collectively ensure that business goals, company practices, and technology implementations are in sync.

“The companies that have integrated data into their business strategies see it as a means of growing their businesses. They use it to differentiate themselves by providing customers with better service, quicker turnaround, and other things that the competition can’t meet,” said Ken Gilbert, director of business analytics at the University of Tennessee’s Office of Research and Economic Development, in an interview with InformationWeek. “They’re focused on the long-term and big-picture objectives, rather than tactical objectives.”

Uncovering Opportunities

Enterprises have been embracing BI and big data analytics with the goal of making better decisions faster. While that goal remains important to data-driven enterprises, they also are trying to uncover risks and opportunities that may not have been discoverable previously, either because they didn’t know what questions to ask or because previously used technology lacked the capability.

According to Gartner research VP Frank Buytendijk, fewer than half of big data projects focus on direct decision-making. Other objectives include marketing and sales growth, operational and financial performance improvement, risk and compliance management, new product and service innovation, and direct or indirect data monetization.

Hypothesis Trumps Assumption

People have been querying databases for decades to get answers to known questions. The shortcoming of that approach is assuming that the question asked is the optimal question to ask.

Data-driven businesses aim to continuously improve the quality of the questions they ask. Some of them also try to discover, through machine learning or other means, what questions they should be asking that they have not yet asked.

The desire to explore data is also reflected in the high demand for interactive self-service capabilities that enable users to adjust their thinking and their approaches in an iterative fashion.

Pervasive Analytics

Data analytics has completely transformed the way marketing departments operate. More departments than ever are using BI and other forms of analytics to improve business process efficiencies, reduce costs, improve operational performance, and increase customer satisfaction. A person’s role in the company influences how the data is used.

Big data and analytics are now on the agendas of boards of directors, which means that executives not only have to accept and support the use of the technologies, they also have to use them — meaning they have to lead by example. Aberdeen’s 2014 Business Analytics survey indicated that data-driven organizations are 63% more likely than the average organization to have “strong” or “highly pervasive” adoption of advanced analytical capabilities among corporate management.

Failure Is Acceptable

Some companies encourage employees to experiment because they want to fuel innovation. With experimentation comes some level of failure, which progressive companies are willing to accept within a given range.

Encouraging exploration and accepting the risk of failure that accompanies it can be difficult cultural adjustments, since failure is generally considered the opposite of success. Many organizations have made significant investments in big data, analytics, and BI solutions. Yet, some hesitate to encourage data experimentation among those who are not data scientists or business analysts. This is often because, historically, the company’s culture has encouraged conformity rather than original thinking. Such a mindset not only discourages innovation, it fails to acknowledge that the failure to take risks may be more dangerous than risking failure.

Data Scientists And Machine Learning

Data-driven companies often hire data scientists and use machine learning so they can continuously improve their ability to compete. Microsoft, IBM, Accenture, Google, and Amazon ranked first through fifth, respectively, in a recent list of 7,500 companies hiring data scientists. Google, Netflix, Amazon, Pandora, and PayPal are a few examples of companies using machine learning with the goal of developing deeper, longer-lasting, and more profitable relationships with their customers than previously possible.

Crafting the Ultimate Email Interview Response

email-824310_640More journalists have moved to email interviews, including this one.  You’d be surprised how different the responses are, and IMHO, it’s the little things that can make or break coverage.

This post assumes your client has been selected for an email interview.

#1:  Include Your Client’s Information

Wait, what?  I already gave you that stuff in my original pitch over email…

Maybe, but is it correct?  A lot of times in a pitch, PR pros will say something like, “Anil is with…” or “Anil is lead at XYZ Company.”  That may be true.  On the other hand, his LinkedIn title, or the title on the company site (assuming he’s listed) may say something more specific like VP of Technology and Co-founder.  Perhaps he was just promoted to CEO and it hasn’t been announced yet, but will be by the time the story hits.  Stuff happens.

Include your client’s information so you can be sure that it’s correct and free of typos.  Sometimes email pitches include typos that include misspelled client names or misspelled client company names (which happened this week).  Also, in the unlikely event that your client’s name or company name is misspelled when the story hits, you can show the mistake wasn’t yours (which makes a difference).

And another thing:  Sometimes an email thread related to a pitch for ONE story is unbelievably long.  Some of them exceed 20 messages to and from Ms. PR Maven.  She may have included the client’s title in Message #1, in Message #19, somewhere in between or not at all.  It’s cheap insurance (and a best practice) to include your client’s information at the top, in boldface type, with a link to your client’s website.

#2:  Advise Your Client to Provide Thoughtful, Well-Reasoned Responses

Most interviewees do this, which is great.  A few don’t.  Those that don’t run the risk of not being included in a story because what they said just doesn’t fit in.  FWIW, at the top of my email interview questions I say, “Thank you for your thoughtful, well-reasoned responses.”  The implication is provide short answers at your own risk.

From where I sit, stories have a life of their own.  I pitch ideas, get approval, fish for sources on HARO, interview people, and then weave that into something coherent.  It’s kind of like putting together a puzzle: I know the subject matter of the puzzle, but I don’t know what the pieces are (depends on the interviews) and how they’ll fit together.  Here’s why brief commentary is dangerous, if you’re working with me.

As background, brief commentary takes a couple of forms – the pithy response and the general short answer, both of which can be difficult or impossible to include in a story.

Knowing journalists use quotables, sometimes (albeit rarely), an interviewee will try to provide short, pithy, supposedly quotable quips that are “cute” and most likely unusable.  The quips are based on false assumptions about how the story will flow.

Comparatively, thoughtful, well-reasoned answers provide perspectives and the reasons for those perspectives.  This is great because intelligent minds, and even experts, disagree.  It’s always helpful to understand why.  Also, the richer commentary also provides more to work with, and therefore more opportunities (and a better likelihood) for coverage.

The general short answer typically shows a lack of effort.  The interviewee provides one or two sentences, which tend to be obvious points that others have also made and so there’s nothing original.  Because there’s nothing original (and someone probably said the same thing more eloquently), guess what?

Obviously, when I don’t use commentary I get questions about it.  I answer those questions honestly, and essentially say one of the two things above.

#3:  Make Sure The Answers Align With the Questions

This sounds obvious, but people can go off on tangents.  Sometimes, I’ve hit a hot-button issue to the point of opening Pandora’s Box.  The interviewee spews out all kinds of information, perhaps little or none of which address the question directly.

Sometimes people want to promote their products.  This is fine to some degree, assuming that’s the point of the piece, but I don’t tend to write about products or how great they are unless it’s sponsored content.  My Help a Reporter Out (HARO) posts always state “non-promotional” content, but not everyone pays attention.  If I ask for commentary on issues and trends, and receive answers about all the bells and whistles of a product, I find myself explaining why the commentary wasn’t used.

Related to this are transparently obvious self-serving answers.  I don’t blame vendors for this.  They’re doing it because PR is a promotional vehicle, but it ain’t advertorial.  Sometimes, transparently promotional stuff is kind of amusing, but perhaps unusable.  I’m really not going to quote someone saying, “what they really need is the industry’s most robust, scalable, global, award-winning, industry-leading API platform.”

Bottom Line

There are a few simple things that can make the difference between getting coverage and not getting coverage.  I’ve included three things that could help probably 40% of the people I work with over time.

If you’re already doing these things, thank you very much.  Hopefully this commentary will be valuable for you nevertheless, because even if you know the ropes, you’ll probably need to teach someone else, soon.

Tech Buying: 6 Reasons Why IT Still Matters

ErrorOriginally published in InformationWeek, and available as a slideshow here.

Making major tech purchases, especially big data analytics and business intelligence tools, without consulting IT may cause major problems. Here’s why.

Although shadow IT is not new, the percentage of business tech purchases made outside IT is significant and growing. When Bain & Company conducted in-depth interviews with 67 marketing, customer service, and supply chain professionals in February 2014, it found that nearly one-third of technology purchasing power had moved to executives outside of IT. Similarly, member-based advisory firm CEB has estimated that non-IT departments control 30% of enterprise IT spend. By 2020, Gartner estimates, 90% of tech spending will occur outside IT.

There are many justifications for leaving IT in the dark about departmental tech purchases. For one thing, departmental technology budgets seem to point to departmental decision making. Meanwhile, cloud-based solutions, including analytics services, have become more popular with business users because they are easy to set up. In addition, their relatively low subscription rates or pay-per-use models may be more attractive from a budgetary standpoint than their traditional on-premises counterparts, which require significant upfront investments and IT consideration. Since the cost and onboarding barriers to cloud service adoption are generally lower than for on-premises products, IT’s involvement may seem to be unnecessary.

Besides, IT is busy. Enterprise environments are increasingly complex, and IT budgets are not growing proportionally, so the IT department is resource-constrained. Rather than waiting for IT — or complicating decision-making by getting others involved — non-IT tech buyers anxious to deploy a solution may be tempted to act first and answer questions later.

However, making tech purchase without IT’s involvement may result in unforeseen problems. On the following pages, we reveal six risks associated with making business tech purchases without involving IT.

1. Tech Purchases Affect Everybody
Tech purchases made without IT’s involvement may affect IT and the IT ecosystem in ways that someone outside IT couldn’t anticipate. You might be introducing technical risk factors or tapping IT resources IT will have to troubleshoot after the fact. To minimize the potential of unforeseen risks, IT can perform an in-depth assessment of your department’s requirements, the technology options, their trade-offs, and the potential ripple effect that your tech purchase might have across the organization. This kind of risk/benefit analysis is important. Even if it seems like a barrier for your department to get what it wants, it’s better for the entire organization in the long run.
Also, you may need help connecting to data sources, integrating data sources, and ensuring the quality of data, all of which require specific expertise. IT can help you understand the scope of an implementation in greater detail than you might readily see.

2. Sensitive Information May Be Compromised
Information security policies need to be defined, monitored, and enforced. While it’s common for businesses to have security policies in place, education about those policies, and the enforcement of those policies, sometimes fall short. Without appropriate precautions, security leaks can happen innocently, or you could be opening the door to intentional bad actors.
Cloud-based services can expose organizations to risks that users haven’t considered, especially when the service’s terms of use are not understood. Asurvey of 4,140 business and IT managers, conducted in July 2012 by The Ponemon Institute and sponsored by Thales e-Security, revealed that 63% of respondents did not know what cloud providers are doing to protect their sensitive or confidential data.

3. Faulty Data = Erroneous Conclusions
There is no shortage of data to analyze. However, inadequate data quality and access to only a subset of information can negatively impact the accuracy of analytics and, ultimately, decision making.
In an interview with InformationWeek, Jim Sterne, founder of the eMetrics Summit and the Digital Analytics Association, warned that the relative reliability of sources needs to be considered since CRM system data, onsite user behavior data, and social media sentiment analysis data are not equally trustworthy.
“If I’m looking at a dashboard as a senior executive and I know where the data came from and how it was cleansed and blended, I’m looking at the numbers as if they have equal weight,” he said. “It’s like opening up a spice cabinet and assuming each spice is as spicy as any other. I will make bad decisions because I don’t know how the information was derived.”

4. Not Getting What You Bought
Similar products often sound alike, but their actual capabilities can vary greatly. IT can help identify important differences.
While it may be tempting to purchase a product based on its exhaustive feature set or its latest enhancements, feature-based buying often proves to be a mistake because it omits or minimizes strategic thinking. To reduce the risk of buyer’s remorse, consulting with IT can help you assess your current and future requirements and help you choose a solution that aligns with your needs.

5. Scope Creep
Business users typically want immediate benefits from big data, analytics packages, and BI systems. But, if the project has a lot of technological complexity — and particularly if it involves tech dependencies that are outside the control of your department — it’s often best to implement in phases. Approaching large initiatives as one big project may prove to be more complicated, time-consuming, and costly than anticipated.
IT can help you break a large, difficult-to-manage project into several smaller projects, each of which has its own timeline and goals. That way, you can set realistic end-user and C-suite expectations and effectively control risks. Phasing large projects can also provide you with the flexibility you need to adjust your implementation as business requires.

6. Missing Out On Prior Experience
IT professionals and outsourced IT resources often have prior experience with BI and analytics implementations that are specific or relevant to your department. Some of them have implemented solutions in other companies, departments, or industries and have gained valuable insight from those experiences. When armed with such knowledge, they can help you understand potential opportunities, challenges, and pitfalls you may not have considered which can affect planning, implementation, and the choice of solutions.

Does HARO Really Work?

HARO logo

HARO: Just a Medium

PR pros sometimes tell me that Help a Reporter Out (HARO) doesn’t work. I would argue the opposite, based on extensive experience with it and the ongoing relationships I’ve established through the medium.

There was some sort of batch-related technical glitch that kept me from receiving about 10 pitches yesterday, but that’s nothing – and certainly not an indication of its lack of usefulness – especially when you consider I’ve been using the medium every week for the last year.  You may or pay not know that ProfNet and HARO are merging, and every merger has technical glitches.

That’s not the reason people have been complaining over the last year.  The reason they’re complaining is twofold:  a lot of journalists are unresponsive and I imagine they’re not getting the results they want.  Ergo, HARO doesn’t work.  OTOH, who’s fault is that?

Don’t Confuse the Medium and the Message

HARO is a medium, nothing more.  It’s just a website or “marketplace” that connects journalists with potential sources and their PR reps.  Blaming HARO for the way journalists behave or the outcome of pitches is like blaming your toothbrush for failing to do a root canal.

On the other hand, I know how frustrating pitching can be.  Been there, done that.  I still do it.  I  understand how frustrating it is when people don’t respond to a pitch, or they’re just plain rude.  It happens to all of us.  However, that kind of stuff happens to some people more often than others – with or without HARO and here are a few reasons why:

You’re Playing the Numbers

If you send a pitch out to a sea of people, it’s likely someone will bite no matter how good or bad the pitch is.  I see people using this tactic as evidenced by pitches that do not directly relate to  a query I’ve posted.  A good example are the fashion pitches I’m getting out of Europe.  Guess what?  Fashion isn’t my beat, not even close.

I usually tell people it’s not my beat, hoping they’ll get the message and stop pitching me.  Although, the more fashion pitches I get, the more likely I am to ignore them.  They’re irrelevant and poorly targeted.  Of all the pitches I get, these are the ones I’ll most likely ignore.

You’re Advancing an Agenda

Well, of course you’re advancing an agenda.  That’s why companies hire agencies and independent PR pros.  OTOH, people often try to advance an agenda that isn’t in line with the specific direction of a story.  And in most cases, it makes no sense to try to shoe-horn a bolted-on topic into the story.

The most common form this takes in my experiences is product-related pitches that are responding to an issues-oriented query.  I get that a lot.  “XYZ company would be happy to tell you why business leaders today need [our client’s product capabilities, including these specific features and functions].”  OK, but I’m actually interested in the personality traits of a data scientist, for example.

Alternatively, I can get things that may seem logical to the person who is pitching, but are not relevant in fact.  An example of this would be, “I see you’re writing a piece on data science.  My client hosts grade school biology science camps.”  The word, “science” is common to both topics.  A pitch about grade school data science camps would have a better chance of succeeding.

I respond to these types of pitches and tell people why their pitches are irrelevant, but I’m apparently among the minority of journalists who do.

Having spent years managing clients and account groups at agencies, I know exactly why people are being trained to do these kinds of pitches – it’s just one tool in the toolbox. The theory is, if you pitch something related to a story, you may succeed.  “May” is the operative word.

You Want the Story Angle Changed

This is a very unlikely outcome, especially when there’s an editorial hierarchy and the writer or editor has already sold an idea to her editor.  A couple of people try this tactic on me every week and it doesn’t work.

The inherent flaws in this tactic are 1) it sends the message that the original story angle is flawed, weak, or or without merit; and 2) the client agenda is usually as transparent as freshly-polished glass.

People pitching themselves tend to do this more.  Don’t write about THAT topic!  Write about me!

It’s Time the Journalist Covered Your Client

After pitching a journalist on the same client time and again, one gets to the point where one feels it’s about time this journalist got with the program.  After all, the journalists’s beat is X and your client fits squarely within the realm of X.  In one of the areas I cover, an industry analyst recently told me there were 2,000 companies he could possibly include in a report but there was only room for 20 or so.  Yikes.

I like to hear from fresh voices assuming the pitch is on-target.

One tenacious young lady who pitches me often had a hit rate of 0 (with me at least).  She pitched me almost every week about the same client and same basic angle.  It wasn’t a fit…until it was.

There were a sea of other pitches that also would have worked but I chose hers over some others because she had the fortitude to stick with it until she succeeded.  I admire her tenacity.  On the other hand, had her pitch been off-base – yet again – I would have passed on it.

Whether it’s “time” to cover a company, topic, product, or whatever is a matter of opinion.  Your opinion won’t align with all the people all the time, but don’t give up.  The most important thing is to learn from your experiences.

Got HARO Horror Stories?

Share ’em.  I’d love to hear about ’em.

Why You Should Fire Your PR Agency. Now.

puzzle-432569_640PR agencies are inefficient in ways that are not apparent to their clients.  The inefficiencies can cost you tens or hundreds of thousands of dollars, and the only “insight” you’re going to have is a rising level of frustration.

One problem is the way PR agencies are organized.  The other has to do with philosophy and people.

PR Agencies May Be Structured Inefficiently

PR agencies have historically been hierarchical organizations.  That’s not true of all PR agencies since the general business trend has been to replace hierarchical organizational structures with flat or matrix structures, but a lot of PR agencies are still structured the same old way.

Typically, your “PR team” includes several people, if your budget allows it.  The most junior people handle the rote stuff and more senior people oversee what they do.  While that operational process is not always inefficient, consider in-house agency meetings.

In-house agency meetings sometimes involve the entire team dedicated to a client.  A one-hour meeting is the sum of all their billable rates, which, if you add them up may astound you.  For your sake, I hope such meetings are fruitful.

Hierarchical structures also fuel egos in a way that is not in the best interest of clients.  Quite often, as people move up the agency ladder, they rid themselves of tasks that tend to be assigned to more junior people.  Depending on what’s happening on the client side, that hands-off mentality may work against the client, especially when a sensitive issue arises such as a product recall, a security breach, or a public attack by a competitor.

They’re Clueless

The typical agency-client relationship looks something like this:  The client is the subject matter expert and the PR agency is the media expert.  It’s a very simple formula that sounds good and is flawed.

For one thing, the client contact may or may not be a subject matter expert.  If the client contact is a subject matter expert – great, especially if the PR reps are actively listening, taking notes, and asking smart questions.  If the client contact is not a subject matter expert, few PR pros will be able to tell because their domain knowledge is either weak or non-existent.  That’s one way misinformation gets propagated.  Everywhere.

Worse, a lot of PR pros don’t understand their clients in any real depth, which I think (and I have always thought) is a mistake.  There are a few reasons for that:

It’s not my job.  Most PR pros don’t take the time to understand their clients and their clients’ products or services because they don’t consider it part of their jobs, as unbelievable as that may seem.  After all, the client is the subject-matter expert.  The problem with that philosophy is that journalists often ask second-level questions that few PR pros are prepared to answer such as, “Why do I need a smartwatch if I have a FitBit?”  If they can’t answer basic questions, you’re likely losing coverage at your expense.

It’s not billable.  Coming up to speed takes time, and the question is, who’s going to pay for it?  Clients generally don’t want to pay to educate agency reps.  Agencies don’t want to invest in fishing expeditions ad infinitum, especially if the time spent isn’t billable.  There’s a balance.  Finding it can be tricky.

They’re green.  Most PR pros on the front line are very young.  They lack the life experience and work experience necessary to infer important insights and ask insightful questions.  It’s not their fault.  They’ll learn eventually,  most likely at your expense or another’s client’s expense.

They lack passion.  Some PR pros aren’t passionate about what their clients do, and when they’re not passionate, they’re not interested, and they’re not doing the best job they could possibly be doing.  In my role as a mentor, some PR people have told me they have a feeling they should be doing something else because they’re uncomfortable with their clients’ subject matter.  These people tend to disappear on their own terms – or on the agency’s terms – in relatively short order.

Good PR People Are Golden

Generally speaking, agencies and people who work for agencies vary greatly in their abilities.  Sadly, clients end up paying for a lot of inefficiencies that are not obvious (even to the people who work in agencies).

My advice is observe the people who are on your PR team and make your own assessment.  You should be able to tell from words and deeds who “gets it” and who doesn’t.  If you have a team full of people that doesn’t get it, it may be time to review your options.

On the other hand, it may be time to look in the mirror.  Quite often the reason agencies fail or people at agencies fail to grasp critical information is because their client contact doesn’t want to share it, for fear of spilling trade secrets, or for political reasons (information is power).  If you’ve had the same issues over and over again from agency after agency, perhaps the agency isn’t the problem afteer all.

The Accidental Journalist


The Accidental Journalist

Who becomes a journalist “accidentally?”

I, for one, and you’ll never guess how.

It was 1994.  I was running PR and advertising for Interop, a huge information technology event.  At the time, it was my job to know all the editors-in-chiefs of the magazines that mattered, when printed publications were the norm.  I could foresee, based on the technologies of the day, that the World Wide Web had the potential to be more than a collection of digital brochures.  It was going to become a medium through which people would buy things. (I’m sure that sounds obvious if not incredible to you now, but it certainly wasn’t obvious to many people at the time.)

Armed with my flash-from-Heaven insight, I tried to convince every editor I knew that e-commerce was going to be The Next Big Thing.  I wasn’t looking for a writing gig.  I was trying to clue them into one of the biggest news stories of the time.  None of them believed me.  Finally, the editor of Internet World said, “I don’t believe you either, but write a story and let’s see what happens.”

What happened was nothing short of amazing.

Two publishers contacted me, asking to contribute e-commerce chapters to books they were publishing.  Soon thereafter, I chaired and helped plan an oversold e-commerce conference that attracted more than 500 professors and executives of some of the world’s largest corporations in Japan.  It was an unexpectedly great start to my eventual role as a journalist- certainly one I never expected.

I guess in my case, the ghost came out of the closet, although yes, I am still ghostwriting.  I am also writing under my own name for publications including InformationWeekSD Times, and All Analytics.  And, you can look forward to hearing more from me here.

Got questions or topics you’d like me to address in this blog?  Feel free to speak out in the comments section below or use the form on the Contact Me page.

Oh, and I teach writing workshops 1:1 and to groups at PR agencies in case you’re interested.