[Moved from brendamichelson.com. Original publish date: May 29, 2018] Back in January, I was asked to participate in PEW Research’s survey on the impact of digital life: “Over the next decade, how will changes in digital life impact people’s overall well-being physically and mentally?” The choices: more helped than harmed, more harmed than helped, not […]
Like many with corporate IT backgrounds, I find the do-it-yourself (DIY) technology movement simultaneously intriguing and frightening. Intriguing, because of the ease of connecting with co-workers, partners, customers and information to solve problems, improve interactions and advance the business. Frightening, because I’ve lived through (barely) the data, network and integration nightmares brought on by islands of Access, Excel, FileMakerPro, Visual Basic, etc.
Of course, today’s DIY technologies – Smart mobile devices, Pervasive video, Cloud computing services and Social technologies – are exponentially more powerful than their office productivity predecessors. Therefore, they must be exponentially more troublesome, right? Well, that depends.
In Empowered, a new book by Josh Bernoff (co-author of Groundswell) and Ted Schadler of Forrester Research, the authors address this very challenge, how to balance front-line innovation with back-room risk management. Or, as the authors describe it, changing the way your business runs to harness the power of HEROes: highly empowered and resourceful operatives.
Following an attention grabbing introductory section, the book’s guidance is presented in two more parts. In part two, the authors focus on HERO projects, describing opportunities and challenges, elucidating with real-world examples, sharing tools and walking through a four-step process to match-up with that other critical DIY base, your empowered customers.
A helpful tool is the HERO Project Effort-Value Evaluation. After answering a series of questions on a potential projects effort and value, you calculate your projects EVE score. Scores fall into one of six categories, from no-brainer (value exceeds effort by 25 points) to shadow IT (high effort). On the Shadow IT projects, the authors don’t say never, however they point out the risk factors, success impediments, and advise collaboration with senior management and IT.
In part three, the authors discuss how management, information technology and HEROes work together to achieve that all important opportunity-risk balance.
The critical concept in part three is the establishment of a HERO Compact. The HERO Compact is an accord between management, information technology and HEROes, guiding each group’s behavior to make “HERO-powered innovation successful”.
In the spirit of empowerment, I’ve clipped the high-level HERO Compact from Amazon’s Search Inside this Book.
The chapter continues with specific pledges for IT, management and HEROes. Each pledge reinforces that success requires individual responsibility, collaboration and trade-offs.
For example, the IT Pledge includes: “I will respect requests for new technology support and find ways to say, “Yes, and” rather than automatically saying “No.”.
The HERO Pledge includes: “If my projects entail a significant effort, I will work with my managers and IT to better understand the long-term impact of those projects”.
And the Management Pledge includes: “I will respect assessments of technology risk in HERO projects and work with IT and others to quantify, mitigate and ultimately manage that risk”.
Empowered does a nice job of describing the compelling workforce and customer benefits of embracing DIY technologies, while painting a realistic view of the traps and risk, and offering pragmatic advice and tools for prospective HEROes, managers and IT to co-create a front-line innovation environment.
Organizations struggling to keep up with their customers, employees or competitors on the DIY technology revolution need to read Empowered and think seriously about HERO Compacts.
[Disclosure: Forrester sent me a free “no obligation” copy of Empowered.]
Mike Loukides has an excellent piece on O’Reilly Radar entitled “What is data science?” In the article, Loukides covers making data products, the data lifecyle, working with data at scale (Big Data), story telling and data scientists.
Throughout the article, Loukides introduces the reader to many data science concepts, tools, experts and skills.
Calling out several items, I love the “data exhaust” term:
“These recommendations are “data products” that help to drive Amazon’s more traditional retail business. They come about because Amazon understands that a book isn’t just a book, a camera isn’t just a camera, and a customer isn’t just a customer; customers generate a trail of “data exhaust” that can be mined and put to use, and a camera is a cloud of data that can be correlated with the customers’ behavior, the data they leave every time they visit the site.”
I think this “make lemonade” sentiment on data quality is crucial:
“Once you’ve parsed the data, you can start thinking about the quality of your data. Data is frequently missing or incongruous. If data is missing, do you simply ignore the missing points? That isn’t always possible. If data is incongruous, do you decide that something is wrong with badly behaved data (after all, equipment fails), or that the incongruous data is telling its own story, which may be more interesting? It’s reported that the discovery of global warming was delayed because automated data collection tools discarded readings that were too low 1. In data science, what you have is frequently all you’re going to get. It’s usually impossible to get “better” data, and you have no alternative but to work with the data at hand.”
The big data definition is excellent. It’s about the problem, not the (product) solutions:
“The most meaningful definition I’ve heard: “big data” is when the size of the data itself becomes part of the problem. We’re discussing data problems ranging from gigabytes to petabytes of data. At some point, traditional techniques for working with data run out of steam.”
And the information platforms / dataspaces concept ties to my active information tier:
“What are we trying to do with data that’s different? According to Jeff Hammerbacher 2 (@hackingdata), we’re trying to build information platforms or dataspaces. Information platforms are similar to traditional data warehouses, but different. They expose rich APIs, and are designed for exploring and understanding the data rather than for traditional analysis and reporting. They accept all data formats, including the most messy, and their schemas evolve as the understanding of the data changes.”
If you want to learn something today, read the article. Then bookmark it for future reference.
I’m at the MIT CIO Symposium today. Currently, I’m in the Internet of Things Panel.
Moderator: Dr. Michael Chui, Sr. Fellow McKinsey Global Institute
- Mr. Robert LeFort, CEO Ember
- Prof. Sanjay Sarma, Professor and Former Chairman of Research and Co-Founder of The Auto-ID Center at MIT
- Mr. Bob Metcalfe, Partner Polaris
- Mr. Mark Roberti, Editor RFID Journal
Sanjay Sarma – Started in 1998, vision similar to Internet of Things today. Given early stage of internet, ambition was to replace barcodes with RFID. Problem was price point. Barcode is a few cents. RFID target was 5 cents. Brought cost of tags down. Made the tags cheap by not putting data on tag, but only a number. The data would be on the Internet, accessible through cell phones. This brought about the Internet of Things.
For example, redo HVAC on this building (MIT Kresge). Lots of resistance, jobs at risk. However, big sustainability gain. The people are most affected by Internet of Things.
Mark Roberti – Heard about RFID accidently. Was covering supply chain tech, Manugistics and i2. Software wasn’t delivering value. Why? Data in was bad. Forecasts ended up bad.
Heard about RFID at a conference, DoD was using on battleships. Energized about space. Began RFID Journal.
Now, tremendous innovation going on. Most impactful application: main application is asset tracking. Applications are exploding: tracking babies to prevent SIDS.
Robert LeFort, Ember – company provides chips and software to actualize vision. RFID value for last 10 years. Now, innovation such as clean tech. “Unbelievable the power of convenience” – Shell Executive.
Utilize RFID for energy, utility usage controls in way that is simple and convenient. Use the proper amounts of energy at the best savings. Get big payback. Don’t want notification to turn off appliance. Want smartness in appliances and reduced energy bill.
Bob Metcalfe – Now an investor. One investment is Ember. Looking for opportunities: education, energy and healthcare. Embedded (Internet of Things) is space across those.
10 – 15 billion microcontrollers being shipped every year. Not tags. Most are not networked. Humorously infers to Metcalfe’s Law. Needless to say, there’s an opportunity here.
Invested in node and tag companies, including Sticky Bits.
Mark – Term Internet of Things is very valuable, but has outlived usefulness. Allows us to see track and manage things we haven’t been able to see, track and manage previously.
Sanjay – dealing with the data deluge – enterprise systems today, such as RFID, aren’t designed to receive feedback. What happens when have wrong number of pallets of toothpaste?
Most important thing to do with RFID data is “use it or lose it”. Data rots. Short shelf-life. Can fix pallet before truck leaves. Otherwise, data is forensics.
Robert LeFort – Role of CIO and IT in Internet of Things. Convergence on Internet is a good thing. CIOs know how to manage, exploit Internet.
From here, the discussion went into a lightening round. Next areas of opportunity are health, vehicle, and managed home. See big uptake in US and China. Of existing companies, only Cisco mentioned as having opportunity to lead/exploit RFID. See RFID as both B2B and B2C play.
The audience Q&A is focused on implementation characteristics (data processing and passive tag range), use cases (food lineage) and future advances.
For more insights from MIT CIO Forum, check out the twitter stream #mitcio.
As I mentioned on Monday, I spent a couple of days this week at Cloud Connect in Santa Clara for some upfront cloud watching. The conference was spilling over with the clouderati — those visionaries, strategists, technologists and analysts at the forefront of cloud computing.
It was literally, the cloud computing twitter stream come to life. As such, much of the conference conversation is captured in twitter, under the #ccevent tag.
I did blog from a few sessions, links to those posts follow:
- @ Cloud Connect: Tuesday Morning 10 Minute Keynotes
- @ Cloud Connect: The Surprising Economics of the Cloud
- @ Cloud Connect: Public, Private, or Hybrid: Where’s the Value Today and Where’s It Going?
Mostly though, I took the opportunity to absorb the ideas presented and engage in conversation with fellow attendees.
I’ll do a summary of my observations soon, but wanted to pass along these links now. Cloud Connect is “the” cloud computing conference. I look forward to future editions.
I also had a chance to attend a special session of the San Francisco Cloud Club, which focused on PaaS platforms. The decision considerations presented by Engine Yard and Heroku really make you appreciate the difficulty of the work that PaaS providers do on behalf of adopters.
These are definitely interesting times, and not in the curse sort of way.