Good read. Find out what other small businesses are using to mine big data they can afford and use.
Excerpt: When Kobie Fuller was hired as chief marketing officer at Revolve Clothing, in July 2011, one of the major challenges he faced was how to encourage customers to become repeat buyers.
He was sure that the answer lay somewhere in the mass of customer-order data the 160-employee online apparel retailer collects daily. But when he arrived, that data was stored in a difficult-to-navigate database. Pulling sets of data meant asking an IT guy to run a special query. And even figuring out where to start was tricky. Revolve’s data reached back to when the company was founded, in 2003. “I wanted ready access to key statistics without begging someone to mine the data for me,” says Fuller.
Read full article via Big Data for Small Businesses | Inc.com.
Small business takeaways in the article for enterprise level C-Suite.
Excerpt: …… most enterprises grew up in an era before the importance of data was recognized, such that the part of a company responsible for collecting, storing, and extracting data is often separate from the part responsible for using the data. This structural separation makes it difficult to implement data solutions across an organization.
Enter the Chief Data Officer. Making the most of a company’s data requires oversight and evangelism at the highest levels of management. The CDO would be responsible for:
Read full article via Your C-Suite Needs a Chief Data Officer – Anthony Goldbloom and Merav Bloch – Harvard Business Review.
Good read. I think the article helps to put data in perspective for the rest of us.
Excerpt: You recently launched Hack/Reduce — a sort of Big Data playground — in collaboration with MIT, Harvard, and other Boston-area universities. What was the inspiration behind it?
Fred Lalonde: We started Hack/Reduce in response to two big barriers to using Big Data. One is scalability. You can’t do Big Data on your laptop. You need 1,000 computers. The second is finding people who have the training, knowledge and expertise to work with Big Data. Even in a city like Boston, with the depth of software talent, there was literally nowhere where people with an idea could boot up enough computing power to try it.
We started with a one-day hack-a-thon and invited people to come over. The premise was you say to geeks: “We’re booting up all the computing power you need to come and do whatever you want.”
Read full article via What Could You Accomplish With 1,000 Computers? – Dana Rousmaniere – Harvard Business Review.
Good read and takeaway how-to. Big Data for many is overwhelming, particularly when it comes to management and utilization. However, in order to remain competitive, we need to develop best practices and the more information we have of “discovered” tips and advice, the better.
Excerpt: Large-scale data gathering and analytics are quickly becoming a new frontier of competitive differentiation. In a recent Harvard Business Review article we explore how companies require three mutually supportive capabilities to fully exploit data and analytics: an ability to identify and manage multiple sources of data, the capacity to build advanced analytic models, and the critical management muscle to transform the organization.
Getting started on a successful data and analytics journey, however, is a continuing challenge for many leaders and they often struggle for a clear strategy that ties data and analytics to improved performance. We took a close look at companies that have recently launched big data strategies to shed further light on the tough road C-level executives face. From these experiences, we have distilled four principles to defining a strategy and getting started:
Read full article via Get Started with Big Data: Tie Strategy to Performance – Dominic Barton and David Court – Harvard Business Review.
Good advice as we all trudge through the evolution of data management and data utilization of Big Data for the ultimate best practices tips to help our small businesses.
Excerpt: One can’t help being impressed with the effort biologists, physicists, and other scientists devote to data quality. From careful design of experiments and data collection processes, to explicit definition of terms, to comprehensive efforts to ensure the data are correct, no effort is spared. This is not surprising. After all, data are the lifeblood of science.
Increasingly, data are also the lifeblood of business and government. And the attention science pays to data quality provides important lessons, especially for those interested in “Big Data.”
Simply put, bad data make everything about Big Data — from discovering something truly novel, to building a product or service around that discovery, to monetizing the discovery — more difficult. The two most important problems are:
The data are poorly defined, leading to incorrect interpretations.
The data are simply wrong, incomplete, or out-of-date, leading to problems throughout.
Read full article via How to Repair Your Data – Thomas C. Redman – Harvard Business Review.
With all the articles on Big Data, especially this year, if you haven’t heard of the new expert, Data Scientist, you will. This article gives you some insight into what is a data scientist and why you will need them. Data mining, data management, information technology
Excerpt: There are some great articles about big data and analytics in the current issue of HBR, and I am happy to have co-authored one of them with DJ Patil, one of the world’s first practicing data scientists. In fact, data scientists are what our article is about. I would argue that they are the most important resource for capitalizing on big data. While there is a lot of Hadoopalooza in the technology press about the tools for managing big data, and they are wonderful, it’s also true that they are a) widely available, and b) mostly free. Neither can be said of data scientists. The other necessary resource, massive quantities of data, can also be found on every virtual corner these days. If your customers have internet access, for example, you’ve got big data.
Simply put, you can’t do much with big data without data scientists. They are the magicians who transform an inchoate mass of bits into a fit subject for analysis. God may have been the first to produce order out of chaos, but data scientists do it too, admittedly on a smaller scale. They can suck data out of a server log, a telecom billing file, or the alternator on a locomotive, and figure out what the heck is going on with it. They create new products and services for customers. They can also interface with carbon-based lifeforms — senior executives, product managers, CTOs, and CIOs. You need them.
Read full article via Can You Live Without a Data Scientist? – Tom Davenport – Harvard Business Review.
A webinar for help and how-to use Big Data — the effective data management — for gain.
Excerpt: Historically, companies have decided which markets to focus on and have allocated sales resources based on looking at past results and using gut instincts. But today, “big data” and deep analytical capabilities give sales and marketing leaders a better way to make decisions. Managers now have the ability to use data to precisely identify lucrative micromarkets and better align sales resources to maximize opportunities. Companies that use analytics to pursue a micromarket strategy are dramatically increasing sales without spending more.
In this HBR webinar, McKinsey partners Manish Goyal and Homayoun Hatami describe how to use data to drive sales — without increasing costs.
Check out webinar here via Mining Big Data to Find New Markets – Jason Sylva – HBR Events – Harvard Business Review.
I think we now all agree this is so — and the good news is that the dashboards are becoming weighted useful versus time consuming management tools.
Excerpt: Knowledge is Power
Collection of information is required for every industry. For example, the number of patients seeing a doctor each day or how quickly a waste management company’s employees are picking up refuse are measures that can be tracked to determine how a business is running. Without this intelligence, it is impossible to know what is working, where weaknesses exist and what processes may need to change to ensure the health of the organization.
However, collecting the data is only half the job. If the information is siloed, it cannot be easily viewed or acted upon. If the material is trapped in static computer applications, like spreadsheets, it may only be made available to a limited number of employees. Many companies have found the key to easing this pain is dashboard technology.
Read full article via Dashboards: Data Visualization for all Elements of the Business – Information Management Special Reports Article.
A short but important list again on the challenges of Big Data.
Excerpt: Key Questions To Ask Yourself Before Embarking On A Big Data Journey
Read full article via Key Questions To Ask Yourself Before Embarking On A Big Data Journey | Forrester Blogs.
Another good article on BIG DATA — what it is and what it is not — harnessing and best practices uses. With the evolution of overload information and technologies driving more — most, including small businesses, are striving to “get their head around” the challenges and the benefits.
Excerpt: By contrast, the overwhelming majority of enterprise IT systems can’t quite make up their digital minds. Is big data there to feed the algorithms or inform the humans? Is big data being used to run a business process or create situational awareness for top management? Is big data there to provide a more innovative signal or a comfortable redundancy? “All of the above” is exactly the wrong answer.
What works best is not a C-suite commitment to “bigger data,” ambitious algorithms or sophisticated analytics. A commitment to a desired business outcome is the critical success factor.
Read full article via What Executives Don’t Understand About Big Data – Michael Schrage – Harvard Business Review.
Good read — if you are not struggling with these issues yet — perhaps you have just opened the doors and are not into “business” quite yet — or you live under a rock.
Excerpt: The prospect of employees downloading and mashing up data brings up concerns about data security, reliability and accuracy. But in my research, I’ve found that employees are already assuming more responsibility for the technology, data and applications they use in their work. Employees must understand how to protect sensitive corporate data. And leaders will need to learn to “trust, but verify” the analyses of their workforce.
Ensuring that big data creates big value calls for a reskilling effort that is at least as much about fostering a data-driven mindset and analytical culture as it is about adopting new technology. Companies leading the revolution already have an experiment-focused, numerate, data-literate workforce. Are you ready to join them?
Read full article via Data Is Useless Without the Skills to Analyze It – Jeanne Harris – Harvard Business Review.
Small business great read. The push and choices today can be overwhelming, especially for the small business — how-to make decisions of just enough and the right criteria and tools.
Excerpt: In the last few decades, statisticians and computer scientists have produced a dazzling arsenal of extremely powerful tools to help managers translate data into business decisions.
Having access to a wide array of versatile solutions is not ordinarily considered a problem in the world of business. But the rise of “big data” has also brought along with it the explosion of mathematical models made possible by today’s low-cost computing and storage platforms. Ironically, this poses a number of substantial challenges to managers trying to making sense of ever-growing quantities of information.
For example, says, Wharton PhD student Eric Schwartz, managers may be tempted to, as he put it, “flex their data-science muscles” and use a statistical model that is simply too complicated for the task at hand. The result, he notes, might well be that the model produces bad advice.
Read full article via Finding the Right Tool to Unlock the Power of Data – Knowledge@Wharton.