Asking For Help

For many people, especially clever people, asking for help is hard. Very hard. Like many of you, I enjoy solving problems on my own. I get great satisfaction from solitary problem-solving tasks such as finishing a 1000 piece jigsaw puzzle, mastering a particularly challenging Sudoku or climbing a difficult mountain trail.

There are other kinds of problems that need solving. No, I’m not talking about crossword puzzles, but the fuzzy, complex and nuanced problems faced in business and life. The ones where a worthy solution creates a new crop of problems (or in business-speak, opportunities) that need equally thoughtful consideration.

These problems come in all shapes and sizes. The economic: what is the best use of my abilities? The political: how can I foster peace, understanding and growth in my community? The business: how much money and skills (if any) should I invest into solving a market need or customer problem?

On the surface, asking for help creates the appearance of vulnerability. But a deeper analysis demonstrates that asking for help is one of the most powerful forms of leadership. Why? Because solving fuzzy problems isn’t an individual task. This is mainly because not everyone agrees that there is “a problem” or that a particular “solution” is valuable.

Those who seek to solve these sorts of problems on their own are tilting at windmills. To paraphrase H L Mencken: for every complex problem there is a solution that is simple, neat-and wrong.

Alternatively, asking for help is an opportunity to understand how others feel about the issue. Does the problem need urgent attention? Is a solution vital to others? Sometimes you’ll find out if the problem is correctly framed. For example, is the use of modern phone call recording technology a matter of personal productivity, national security or constitutional rights? No simple answers here.

Asking for help is a chance to get feedback on a potential solution to the problem. If others agree with the solution, you can take a more aggressive step and ask for an endorsement or for resources to further your proposed solution. It is in these important moments that asking for help crosses the line from vulnerability to leadership. It’s important to note that this type of leadership and persuasion brings with it an obligation to further the desired end. I’ll discuss obligations at a later date.

Fuzzy problems need organization, clarification and consensus, not a solitary solution. So the measurable unit of success in asking for help is the degree of support behind the proposed solution. Building support, building a coalition, accumulating resources toward an end involves as much problem-solving attention as any puzzle. And the help, the support, the admiration that you get from others in advancing the solution is mighty satisfying.

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

Ranking

Top 10 Technology Priorities

Ranking

Increasing enterprise growth

1

Analytics and business intelligence

1

Delivering operational results

2

Mobile technologies

2

Reducing enterprise costs

3

Cloud computing (SaaS, IaaS, PaaS)

3

Attracting and retaining new customers

4

Collaboration technologies (workflow)

4

Improving IT applications and infrastructure

5

Legacy modernization

5

Creating new products and services (innovation)

6

IT management

6

Improving efficiency

7

CRM

7

Attracting and retaining the workforce

8

Virtualization

8

Implementing analytics and big data

9

Security

9

Expanding into new markets and geographies

10

ERP Applications

10

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.

Takeaways

  • 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.