Category Archives: Business Intelligence
Business Intelligence Lessons from Yahoo! (Meyer’s decision on working from home) – #video from @AllAnalytics
Working remote can be a challenge, but more and more companies are finding success with it. 37 Signals, the firm that created Basecamp, has its workers mostly remote, with a central core workforce in its Chicago headquarters.
Marissa Meyer, Yahoo’s CEO, chose a different route. She mandated more employees to work at its main headquarters. Since that time Yahoo! has acquired a number of companies, including Tumblr. But its overall financial performance still has been questioned by Wall Street Analysts, according to Forbes. So time may tell if Meyer’s famed mandate inspired a significant change for Yahoo!
But consider this instance as a business intelligence lesson – analytics played into her decision. There are also lesson of treating clients who are remote. Meyer made her decision because log ins were reported low – so being remote implied a sense of inconsistent results, an unwanted characteristic for any business that seeks to improve itself.
Listen to the video and provide your comments here or at the All Analytics site.
This infographic by Boston University displays some basic reminders of why analytics is essential. It ultimately supports business intelligence, and provides guidance into what activity is a competitive advantage for a given business.
I like that this infographic opens with a definition of business intelligence. I also like the highlight of how necessary analytics will be once the internet of things takes off. 2020 is a fair estimate, allowing for variations in how the internet of things will develop. The sources of data will be massive, and refining business intelligence to account for the data sources will be vital for business survival.
Cloudcamp in Chicago is an interesting mix of presentations on technology. Presenters are usually from the same industry, and are timed to keep presentations at 5 -10 minute lengths.
I attended the September 3rd, 2014 gathering at TechNexus, an incubator in Chicago which recently moved to the upper office floors of the Opera House. Four healthcare professionals spoke about technological trends and highlights from their industry, specifically about security (HIPAA), the Internet of Things, data security, and health service development from startups. This set of presentations included:
- Security and Sanity in the HIPAA compliant workplace, Alex Connor, lead architect (@HiTizen)
- We are doctors who take care of patience. What can technology do?, Dr Griffin Myers, Co-Founders and CMO, at Oak Street Health (@OakStreetHealth)
- QS and BioHacking Movements, Mark Moschel (@markmoschel), Chief Technology Officer of Factor 75
- Removing silos in Healthcare Data, Carol Zinder, Vice President, Client Experience at CareMerge
All had fascinating looks at their related issues.
Mark Moschel (@markmoschel), Chief Technology Officer of Factor 75 caught my attention the most with his presentation, QS and Biohacking Movements. His presentation focused on the behavior that has arisen from the budding internet of things era. He spoke about the self-care movement.
You may not have heard of it, but you’ve seen hits of it thanks to consumer-available tech devices that measure glucose levels, heart beats, and other personal metrics. There are two groups of tech enthusiasts that have risen from the self care movement.
One is the Quantified Self Movement. QSM is a belief system of “self knowledge through self tracking”, that users manage aspects of their health through the data they collect. According to Mike, Users:
- collect data
- learn about themselves
Users also talk about what they discovered with others, usually in small groups. Mike showed an image in which several execs and well-known technologists, including Wired magazine editorial founder Kevin Kelly, talking to each other about their own experiences with data collection.
The second group are called the Biohackers. The description sound similar to the first, but in the QSM example, practitioners are seeking ways to manage their health. Biohackers seek to improve themselves. Mark calls this system thinking to control and upgrade their own body. Most of the biohacking occurring centers on novel aspects of health, but the outcome is being better able to track posture, heart, mood, blood glucose. The tech that allows for these metrics are include implantable glucose monitors and digestible pills.
The slides for this presentation and all the others are available on the Cloudcamp Slideshare page – shown below is an embed of the presentation.
This Datacamp infographic compares the popular programming languages for statistical analysis – SPSS, SAS, and R. As more data is issued via APIs and databases, organizations are turning to one or more programming languages. As Datacamp has noted on its blog, a “language war” is underway, with statisticians and programmers debating the merits of their favorite language. This comparison explains well the differences, though there are variations and nuances depending on the purpose of the language. R has been widely adopted because of its open source status, but SAS is supported throughout many industries. But in many cases, programmers and statisticians are using one or more languages.
You can learn about SAS through websites such as All Analytics. R Programming is covered at R-Blog. In the meantime, click on the infographic below to view how SAS, SPSS, and R differ…and compare favorably against each other.
Marketing automation is worth more than a process that advances analytics capability. It has a growing important value in a business strategic plan. Businesses struggle to organize their marketing, typically due to running separate social media, email, and platforms. The effort yields individual results to each platform, but can overlook multichannel opportunities or personalization which more customers crave.
Marketing automation addresses that need by consolidates marketing planning and reduces “clutter” from managing separate media. Planning how to automate can highlight where a message may not need to be repeated as well as how to repeat other messages that are valuable for the customer. The planning with marketing automation as a core function saves time and, when done right, improve marketing results.
Automation has a particular value for small businesses. Small business owners and their employees are busy, leaving a limited time to analyze analytics reports repeated. Marketing automation can streamline resources by automating marketing tasks.
There are three tips small and medium sized businesses can follow to prepare for adding marketing automation features.
- Get a lay of the initial data on the land. Establish the best data possible in the systems that will match up to your analytics. This means eliminating duplicate entries in sources such as CRM systems. Use advanced databases tools where possible to find consistent duplicates and errors.
- Roadmap how data will flow through the organization. Roadmap how an automation program will be implemented. Addressing all digital platforms at once can overlook needed steps. Set a six-month goal for full implementation, with milestones along the way. Use features like an annotation in Google Analytics to journal technical changes – some marketing decisions will trigger other analytics-related decisions such as adjusting tags, setting up remarketing campaigns for certain site visitors, changing filters, or adding custom variables.
- Align your sales and marketing teams to sync promotion communication. Plan the marketing and supporting automation system based on the buying cycle and lead nurturing stages. The sales team’s insight can ensure that your marketing efforts to brand and convert potential customers align with the sales team’s capabilities to execute. This can also indicate how alerts in analytics solutions should be distributed to the teams involved.