10 Qualities a Data-Friendly Business Culture Needs

[ New Perspective ] Tokyo Metropolitan Government Building, Shinjuku, Tokyo, JapanUsing and continuously optimizing data with the long-term goal of providing customer value and increasing conversion sounds easy; it can be difficult to execute. Getting the most from your data requires hard work and a willingness to adapt, to experiment, to learn from mistakes, to correct those mistakes as quickly as possible and to keep doing the process over and over without end. But, no matter the scale, crunching data to generate information and insight is valuable only if the organizational structures are in place to support the effort.

One of the most important problems corporations face is creating, at all levels of leadership a framework of support for and participation in new technologies that can help refine and expand how they do business. As pressure to adopt big data technologies grows stronger, many organizations have understandable fears concerning the integrity of their businesses. At the very least, leadership often perceives these technologies as threats to institutional knowledge and continuity.

Alex Miller of QVC, Anthony Bucci of RevZilla and Slava Sambu of Office Max have offered insight into the benefits of staying current with data processing technologies. They have discussed some of the stumbling blocks they have faced. But, as these three suggest, stumbling blocks are not dead ends. Organizations able to confront problems toward finding solutions soon begin to reap the rewards associated with using data effectively.

One of the goals—and it will become increasingly important—is corporate agility. With the ability to analyze and operate in real-time, a business can be far more responsive to its customers. It can quickly evaluate what is or is not working and correct the problem. It can identify problems and fix them immediately. For example, some data a business collects is going to be “dirty.” This is, and has always been, a common problem. Implementation of information derived from problematic data can potentially create a large problem with a large impact on the bottom line. A company needs to be agile enough to catch these problems, evaluate their nature and devise appropriate solutions as quickly as possible. As in right then; better still, an hour ago. Waiting while information makes its way slowly up the chain as each management level makes a decision—even waiting as long as it takes to organize a meeting of department heads—is not an option anymore.

Businesses are accomplishing this every day, and some have been employing these practices for years, decades. Amazon operates like this. Online newspapers operate like this. Alex Miller’s discussion of the need for immediacy in real-time data management of live broadcasting is particularly relevant. Real-time responsiveness is possible and advantageous with a sympathetic business culture.

What makes for a corporate culture that can successfully welcome and accommodate the emerging landscape of using data?

  1. An ability to understand a data-driven focus can out-perform many, if not all, previous business solutions
  2. An open-mindedness that supports the research, development and experimentation necessary to make best use of big data
  3. A perspective that supports the idea operating in real-time is an excellent way not only to enhance the customer experience but also monitor for problems and quickly correct them. However difficult it can be to negotiate at all levels, business agility is critical
  4. A marketing optimization framework that allows marketers to use the data effectively to make marketing decisions in real-time. Companies with higher conversion rates almost always have better marketing efficiency ratios (net contribution/marketing expenses). These companies understand it’s hard work to accomplish better marketing efficiency ratios, but it’s considerably more lucrative to do so.
  5. Higher standards of accountability throughout the organization, up to and including the CEO. Does the CEO know which factors of the customer experience impact sales, which projects or departments to favor, what truly needs to be done to optimize the marketing efficiency ratio? In a data-driven business climate, the CEO must know these things
  6. Leadership that promotes higher levels of communication, even collaboration, across all teams
  7. A willingness to grant certain decision making powers to smaller teams
  8. A commitment to employing conversion rate marketing principles
  9. An emphasis on making sure data as well as information and insight derived through analytics are flowing to individual teams across the organization so each can make clear decisions and execute in real- or near-real-time
  10. People and processes that foster a culture of risk-taking and ongoing testing

It took very little time to list (or read) these qualities. It will probably take much more time to internalize them so they become ingrained business practice. If you hope to stay competitive, however, just don’t let it take too long.

Revving up a Data-Driven Culture: Anthony Bucci

DSC_0067Three co-founders. A start-up. A long-term commitment to experimentation and testing. Business began to blossom, and today, the organization is entering a period of hyper-growth. This has been Anthony’s enviable experience shepherding www.revzilla.com. In the beginning, nobody needed to convince co-founder Anthony of data’s value, but he has found it’s not necessarily leadership he needs to persuade to make testing and experimenting a company-wide effort.

Anthony has learned letting institutional knowledge for testing reside with top leadership is not an effective organizational strategy. While all levels within a company need to be involved in testing efforts, he encourages businesses to identify a process, define a framework, then “make sure someone with the bandwidth can at least own it.”

Speaking from the position of leadership, Anthony has more to say about fitting data, testing and experimentation into a business’s mindset. Give him a listen.

6 Steps to Begin Using the Data

Steps to Big Data SuccessThe possibilities in big data technology are exciting, but if you know very little about what these information technologies can do for your business, just thinking how to use them can feel like heading out with a plastic straw to fight a behemoth. Can you just walk away from the field? No. Big data technologies are here to stay, and businesses that wish to remain competitive need to embrace a big data mind set. These steps can get you started.

1. Forget the hype.

Every field has its own jargon. Insiders know it, outsiders don’t. It’s awkward to be the outsider still puzzling what data silos are while the jargon-laden conversation you’re listening to has moved on. Don’t let the jargon and all the technology-talk distract you, and definitely don’t let it dissuade you, from your goal.

Consider that ‘big data’ is merely a label people apply to an evolution in technology that provides much more granular information about your audience and allows you to refine—perhaps expand or automate—many of the ways you do business. Because providers of services use this label, it helps you find solutions that take advantage of new technologies. Beyond that, ‘big data’ is simply a slick term that garners attention. Don’t worry about it.

Many of the solutions you might find valuable help solve the same problems businesses have always faced. And, while the scope and scale of what new technologies can accomplish have grown dramatically, the reasons for the solutions have changed little. Trust you will learn the jargon along the way (just look at how familiar you are with the jargon in this simple article!). Trust there are individuals who can help you understand exactly what a big data solution can do for you.

2. Identify your problems.

All businesses have problems that lead to questions about improvement, whether improvement means increasing customer satisfaction or coordinating what you do online with what you do through other channels. You probably know what your problems and questions are. So itemize them, prioritize them. Do you need to find ways to undertake a more sophisticated approach to testing and optimization? Would it really help to automate your search engine strategies and PPC campaigns? Maybe you want to build a review system you can merge reviews with a variety of product-related applications. Perhaps you most want to build a comprehensive cross-selling platform based on relevance. Start with your problems, then …

3. Identify appropriate solutions.

You can employ a good data scientist(s) to help you develop applications in house. Many businesses find it more cost effective to contract with third-parties. Start learning what third-party solutions related to your problem are available. Many will focus on automated and ‘black box’ applications which are often easier to deploy. Talk to other businesses, attend conferences that associations and providers hold, share case stories from others who have successfully incorporated big data strategies. Be a good shopper, and keep in mind, a big data solution may not be the right answer to all of your questions.

4. Take stock of the data available to you.

This is usually an iterative process with identifying your big data solutions. How much in-house data do you have? From where does it come? How easy is it to access? Will you need to start collecting different data? Would it be valuable to start taking advantage of unstructured sources of data? Do you have or will you need to tap into outside data resources? Do you have data resources you never thought of as resources? Intelligence within your business and careful discussions with third-party providers can help you identify the value of what you have and suggest what you need.

5. Educate the people in your business.

Not so long ago, many organizations resisted incorporating analytics into operations. The big data phenomenon is to analytics as a skyscraper is to a house. One of the more difficult problems is getting everyone in your business to agree these new technologies have value and will work. Leadership often worries dramatic changes might fracture the cohesion of the company and change models that have always worked well; these are real and justifiable, if perhaps frustrating, concerns. You may become enthusiastically convinced a big data solution is going to revolutionize your organization’s effectiveness, but the history of institutional intelligence can be a tough nut to crack.

Help other departments understand how these solutions can actually make everyone’s work lives a little easier. Encourage interdepartmental communication and cooperation. Develop presentations and circulate articles so others can see the value of these changes. Reassurance that big data can change the efficiency and efficacy of how people accomplish their tasks without changing the business goals can go a long way to achieving support.

6. Keep an open mind.

An open mind is going to benefit everyone in your business today. It is even more important as you look to the future. In the upcoming years,  as this technology is refined and that technology is invented, the big data landscape is going to expand and change dramatically. Every business needs to pay attention to the evolution of these solutions and be willing to experiment toward optimizing the most effective ways to conduct business.

As you head out, plastic straw in hand, remind yourself that few things feel too big and threatening when you start breaking them down into manageable pieces.

You can do it.