Evidence, Persuasion and Perception

Marketing-speak is littered with all kinds of trite sayings. I was in a meeting today at a business software organization where the words “perception is reality” was uttered yet again. I sat quietly listening to the speakers’ claims. My client does, after all, have experience in the market, with customers and with the technology.

I understand the logic of the truism. If a customer believes something to be true, they will act on their beliefs. In my experience, prospective IT customers are a skeptical bunch. They distrust advertising slogans and sales claims. And for good reason: they’ve been burned by bold claims and vendor promises.

So the real question isn’t “if” the prospective customer believes your claims, but rather how to persuade the customer to conclude that they need your product and services. In other words, what can you do to induce the prospective customer to take the actions you prescribe. These words are easy to say, hard to accomplish. Changing individual behavior is hard to do. Changing the behavior of a large segment of the market is a remarkable accomplishment.

Evidence, I believe, is the strongest tool for persuasion. Evidence comes in many forms: quantitative studies, product demos, customer references, cost/benefit analyses and others. Evidence stands apart from claims in that it is grounded in one or more forms of reality. Typically evidence is tangible. Most importantly, customers can assess and experience evidence on their own terms.

Creating evidence with the power to change market and individual behavior is hard. It is rarely the case that your product aims at a greenfield opportunity and has no relevant competition. People are very much creatures of habit, making incumbent solutions to problems seem acceptable. Evidence however, can shock markets and individuals into action. They may not buy immediately, they may not even fully accept the evidence, but they will use the evidence to test and perhaps alter their perception of reality.

Is perception reality? Perhaps. But if you want to change perception, you better get some evidence.

What Are the Collective CIO Priorities for 2014?

CIO Priorites in 2014? Who knows.For the past several years I’ve blogged about the Gartner Executive Program’s January announcement of Global CIO priorities for the coming year. Gartner would survey 2000+ CIOs and publish the findings. The announcement took the form of two lists. The first was a top 10 business priorities. The second was the top 10 technology priorities. My clients and I found these lists useful in understanding where  IT leaders focused their brain cycles and budgets.

This year, Gartner went a different direction with their January survey announcement,  “Taming the Digital Dragon.

“Digitalization, the third era of enterprise IT, is beginning, but most CIOs do not feel prepared for this next era.”

Yes, there was a large survey of 2,339 CIOs. Yes, they published a few statistics, such as “51 percent of CIOs are concerned that the digital torrent is coming faster than they can cope and 42 percent don’t feel that they have the talent needed to face this future.” However there are no lists, no trends and no basis for discussion.

What’s my take on this, you ask? Gartner is reaching for newer opportunities in strategy consulting for IT. In the process they are shedding a valuable operationally-focused report around vendor, budget and technology priorities within IT. Hey, it’s their decision what to do. I’m just saying that I miss the previous lists of CIO Priorities.

Bill’s Take on Potential CIO Priorities

My best hunch is that some of the following might be on CIOs’ minds:

Bill’s Picks
Prioritizing the “new four:” social, mobile, cloud and unstructured data, along side the “traditional three:” people processes and technology
Becoming as good at rapidly applying data to decision-making as Google and Amazon
Establishing policies to address mobile device proliferation, diversity, management and security
Becoming more hybrid and federated across Mobile, Desktop, Cloud and Data Center computing
Balancing disruptive innovation with operational predictability

What do you think about my list? Where do you think valid data will come from?  How are we going to have a public discussion of business and technology priorities without first having a rigorous data set? I wish I knew.

CIO Priorities for 2013 from 2,053 Industry Leaders

Every year a Gartner survey summarizes global CIO priorities, and every year I take a very close look at the findings.

The most recent survey was conducted in the fourth quarter in 2012 and included 2,053 CIOs. These individuals span 41 countries and 36 industries. I like this annual survey because it is a well designed study into the priorities driving US$3.7 trillion of spending on information technology and personnel.

CIO Priorities: the Findings

Top 10 Business Priorities


Top 10 Technology Priorities


Increasing enterprise growth


Analytics and business intelligence


Delivering operational results


Mobile technologies


Reducing enterprise costs


Cloud computing (SaaS, IaaS, PaaS)


Attracting and retaining new customers


Collaboration technologies (workflow)


Improving IT applications and infrastructure


Legacy modernization


Creating new products and services (innovation)


IT management


Improving efficiency




Attracting and retaining the workforce




Implementing analytics and big data




Expanding into new markets and geographies


ERP Applications


One of my favorite parts of this survey is that the technology executives are asked about business priorities first. They may be propeller heads at their core, but they understand their primary task is to find ways to align technology with business initiatives and drive strategic results. As a result, top line growth, business expansion, cost control and personnel issues are clearly present in the business priorities. The only item that I’m surprised isn’t explicit ed stated in the business priorities is accelerating product cycles and decision-making.

The technology list is dominated by newer technology that has enough of a track record of delivering disruptive results. The heightened priority suggests that these investments are moving from lab experiments to broad deployment. Cloud and mobile are the talk of Silicon Valley; it’s also found, in my estimation, in 6 of the 10 priorities. Multiyear initiatives where the necessity has out-paced results are also on the list: Analytics, Security, Virtualization and ERP.

Large budget items like desktop hardware, software and support, which in many cases are the largest portions of annual budgets are not strategic topics in this years survey. Likewise, vendor relationships and outsourcing aren’t a priority this year as they’ve been in the past.


  • Its going to be a good year for technology in general as top line growth leads the list of priorities
  • Its not just that CIOs are spending on cloud and mobile, their organizations are benefiting from these technologies
  • Enabling agility from the bottom-up is a big opportunity. From mobile and cloud, to analytics and virtualization, and ERP and CRM, technologies that provide productivity leverage across the organization will be easiest to justify
  • Infrastructure investments won’t be slighted. Organizations will strive to move quickly, but with a strong foundation. Security, scalability and maintainability will be built into to major initiatives. This is a correction to previous years where organization were burned by having to spend on remediation and refactoring to fix mistakes of moving too fast.

What do you think? Comments welcome.

Analytical Rigor Trumps Big Data

The Silicon Valley brain trust, from VCs to entrepreneurs to business executives, are all agog with the relatively new phenomenon of big data. It’s clearly an important technology trend at the intersection of internet’s ability to generate massive amounts of data and cost efficiencies involving the storage and processing large data sets.

Big Data

Image by Rachel Jones of Wink Design Studio using: Tagxedo.com.

Funds are flowing into many big data start-ups which are creating powerful systems and tools for enabling new types of decisions aided by big data collection, analysis, workflow and communication. Established tech companies are building connectors to big data systems. And, not to be left out, mainstream businesses are launching internal big data analysis projects.

The big data excitement is clearly a new phenomenon. Its roots come from applied mathematics, forecasting and econometrics. Statistical analysis has looked as data samples, built models, tested hypotheses and simulated outcomes for many years. Businesses have tested everything from pricing proposals to demographics to feature lists with applied math. Weather forecasts and evaluating baseball talent routinely use applied mathematics. Google’s successful business strategy is a triumphant use of applied mathematics.

What’s changing is that technology makes it efficient to collect the entire universe rather than samples. Size has its advantages. Analysis of larger samples improves accuracy. Collecting large samples quickly speeds decision-making.

But this is where we need to be careful. I believe that, in most cases, more value is created through rigorous analysis rather than collecting larger samples. While the cost of data collection is lower than ever, the labor pool capable of rigorous analysis remains fixed in size. Yes, these brains are increasingly working with larger data samples or the full universe.  Their tools and intellect are data size independent.

Invest in Analytical Rigor

Before jumping head-long into big data, I recommend investing in the brain power needed to do rigorous analysis. Analytical rigor is hard…and it takes a major investment of time, personnel and leadership to accomplish. This is a very different effort that making capital investments in computer hardware, software and processes. Creating a culture of analytical decision-making has paid off for Google and the Democratic National Committee.

Anyone can buy big data tools (heck, anyone can download HadoopR and many other big data management and analysis tools for free) and tell their investors they’re using big data. The missing piece that is the commitment to rigorous analysis, to building a team that has the brain power needed to collect the right data, to building valid predictive models that enable profitable decisions.

Once your organization excels at analytical decision-making, expanding into big data is a no-brainer. If you choose to invest in big data without having a foundation analytical rigor, results will likely be illusive.

What is it Like to be Your own Customer?

Häagen-Dazs strawberry ice cream. Ecco shoes. The New York Times. WordPress blogging software. We all have our favorite companies, products and services. Products that deliver exceptional value, services that are reliably great, and companies that are easy to business with.

haagen dazs strawerry ice cream

Photo credit: Haagen Dazs

Now look in the mirror: is your business as consistently excellent as your favorites? If you’re not sure, then you probably have work to do. After only a brief glance in the mirror, I buckled down and got to work.

Benchmarking Customer Experience

I started by taking stock of what I deliver, my uniqueness and the promise I offer. This was the easy part, because I get to define the playing field. Just as you can’t play tennis without lines and a net, you can’t benchmark your business without a measure of capabilities.

The next step was also easy. I examined my “first impression” touch points: my email footer, my voicemail greeting and my home page. Did they match the benchmark I set for my business? I made a few small adjustments to be more consistent, clear and customer-aware.

Finally I talked to customers, prospects and partners. I asked two direct questions:

  • How did our project improve your business?
  • Would you recommend my company to others?

I listened. I wanted to hear about numerical results. Was there more revenue, more leads, repeatable campaigns? I wanted to hear about problems that are now behind them and a clear path toward their exceeding their goals. And finally, I wanted to hear that they’d recommend me to colleagues and friends.

I got exactly the answers I wanted to hear. Honest answers about what we’d accomplished together. In addition to the good things I wanted to hear, I learned about rough spots and frustrations. In other words, I learned that the core value is solid, but there is room for improvement in multiple areas, as there are many popular business areas now a days like casino games, as sites like woo casino 2 specialize in this.

For me, the greatest take-away from this exercise is that I learned I need to be consistent at everything, not just at my core advantage. My customers want excellence everywhere, from an initial proposal to a final invoice, and from a second campaign to ad hoc phone advice. This makes a lot of sense. My favorite companies have a level of consistency and quality across multiple processes and multiple employees. My goals are not just helping customers succeed, but improving my business across all dimensions.

Walking the Walk

Let me be clear. I’m not advocating for perfect products or over-the-top money-losing service levels. I’m merely suggesting that it’s worth benchmarking customer experience and see if it meets your standards. Creating value is the core of what I do very well. By upping my game, I make my business one that my customers respect, rely on and recommend to others.