Please help me support rare cancer research
On Saturday, I’ll be riding in Cycle for Survival to raise money for Memorial Sloan-Kettering Cancer research and I’d love your support.
My friend Alex Marcus was diagnosed two years ago with Ewing’s Sarcoma, a rare bone cancer, but we’re relieved that post chemotherapy he is in remission.
He is dedicated to helping others suffering from this disease so please consider donating!
quick app recommendations
A newly iPhoned friend asked for quick app recommendations… what did I miss? Let me know. Also, screenshots at the end. Apps in no specific order.
Fantastical: Slightly better UI for calendar rather than default Apple app. Has a sophisticated system for turning free text appointments into correct times like “dinner with Melanie 3pm next Wed”. Not free.
Google Maps: The best there is for maps, direction, voice navigation, and traffic. Free text search is excellent for most cities though new and recently changed places can cause errors. Beautiful new interface but some hidden finger gestures take some time to learn. Beware of battery life if you leave navigation on in the background. Free.
Instagram: Quick way to take or make beautiful photos and share them on Facebook etc… You can follow and like pictures from friends or brands and comment on them. It’s owned by Facebook so there is some likely convergence in the future.
Reeder: Great way to read from Google Reader RSS or other sources. It caches articles for offline reading. Easy to share news or blog articles with others or to other services. Needs a way to say mark as read from wherever you have scrolled and above. Not free.
Pocket: Simple mobile application for reading saved articles later. I’ve set it to automatically (via IFTTT) import links I’ve starred in Google Reader and favorited on Twitter. It has a Chrome browser extension for quickly saving articles on the web for later. It quickly caches and formats articles for reading on the phone and offline. Would love to see a Kindle (paperwhite version) application or interface and a way to have the articles pre downloaded without the application open.
GroupMe: Persistent group messaging with light features for current location, liking, and photo sharing. I use it with high school friends and co-worker buds. Not everyone needs to have the application to communicate with the group (you can use SMS/iMessages but it can overwhelm or confuse non-aware users. It’s too slow and it’s annoying when a message pops up as a notification and then you open the app and it slowly fetches that message. It’s owned by Skype and therefore Microsoft so we’ll see what happens to it.
Path: Fun sharing application with a close group of friends. It’s beautifully designed but can be slow and clunky when compared to what you’re used to with Facebook. It’s fun when there is a lot of energy amongst 10-15 people that all know each other. It has some odd sharing post types like when you wake up and what neighborhood you’re currently in. It now can import your activity from Facebook, Foursquare, etc… and has a nice search feature of prior events. I’d love to see it integrated with Timehop.
Google: Amazing voice search that can quickly lead to answers, maps, websites, etc… It’s worth playing with just for fun to see it automatically correct itself based on the rest of the sentence you say aloud. It has quick links to other Google applications as well. I can’t seem to get it to launch Google Maps application from within the app— maybe a bug?
Square Wallet: Quickly pay at places that accept Square payments processing (there might not be too many places in your area) but it’s fun when it works. You can set it up to automatically open a “tab” when you are near a place then you can order and “put it on” your tab. The merchant will see your picture on their iPad (and likely soon phone) and be able to charge your credit card without you touching your phone or wallet. It can be magically when all the pieces are working together.
Mint: If you use mint.com to track personal bank, credit card, loan, investments, then their application is handy. Would love it to update and some frequency in the background and quickly download new data rather than only download on fetch when the application is open. Could have better cash input interface for on the go tracking.
Slice: If you order through Amazon or other online retailers then this is application is a quick way to track order status and delivery times. It annoyingly defaults to read all types of e-commerce from your gmail (like iTunes receipts, paypal, etc…). I’ve manually disabled everything but Amazon in the settings. It’s a junky application and unfocused (spending pie charts by category?!) but helpful for just monitoring package times without manually inputting tracking numbers.
Fidelity: If you happen to be a Fidelity customer, this application is fabulous. It’s quick, has all the functionality of the website, and has reliable check cashing. It’s a home run.
Cab apps: If these are in your city: Uber (professionals and taxis), Lyft (screened regular drivers with noticeable cars), Sidecar (screened regular drivers without noticeable cars). It can make you feel like a magician or king to call a car out of the blue and track it live with your phone. No tipping or cash needed. Just get out of the car when you’re done. A variety of prices and structures.
TripIt: A must have if you travel even a little bit. It reads from your gmail or you can forward your flight, hotel, and rental car confirmations to their email address. It organizes your travel itinerary and can alert you to flight changes, changes in price, and check in times. It makes it easy to share plans with others and is my go to place for all upcoming travel agendas. It’s great day of travel when you need confirmation codes, ticket numbers, or whatever else they might ask.
Squarespace Note: Super quick way to email yourself something (or some notes to some other application). It loads instantly, has a quick interface to type, and you can initiate the send with a flick of the thumb. I use it to email stuff to myself but would love to see an option to send each line as a new task to Asana.
Songza: Fun way to put on music based on mood.
Vine: Quick way to create up to 6 seconds of video and share it. The gesture to start and stop records is incredible straightforward and is one of those duh moments once you see it. It’s all the rage at the moment and I suspect and hope it takes off as the tweet form of video. It’s created by Twitter so watch for deeper integration. See Jordan Cooper’s review.
Google Drive: Quick access and tiny editing functionally for Google docs.
Beejive GT: A free gchat client I use for work on the go. Open to other ideas. Has ads.
Circa: Not totally in love with it but a new way to read news articles that are hand picked and broken into mobile friend articles. Best feature: you can “follow” a news story and get alerted to new updates rather than reread the same news plus a small update on a regular website.
Groupon: Totally biased since I work there but it’s a fabulous app for finding, buying, and redeeming deals for places around you as well as Woot style products and vacation packages. It’s a 5 star app and one of the most success mobile e-commerce business apps around. It’s smooth and location aware. Give it a try.
Etsy: Fun to browse for one off gifts or just to marvel at how quickly it loads and the attention to color and font. Haven’t bought anything yet.
CardMunch: Take a picture of a business card and it uploads it to be digitized and then is quickly sent back down to your phone. Can quickly add the contact to your address book or connect on LinkedIn. It was created by a friend of a friend at CMU and acquired by LinkedIn so I suspect it will remain free.
SignNow: Good for signing documents on the go.
Foursquare: Great app for find what to do when you’re in a city, what to eat when you’re at a restaurant, or what your friends (if they’re techy) are up to. I love this application and use it as an ongoing journal. Leaving tips and having people do them makes me happy. It’s great.
Google+: I don’t use the network for social posting but do enjoy their Hangout multi-way video conferencing.
Podcasts: Apple pushed podcasts into its own app which has become slow and clunky but seems like the go to place to listen to iTunes podcasts. Allows on the go download and streaming and sync’s with the computer when on WiFi.
Chrome: Would love to see it more deeply embedded into the OS but that’s a long shot given Apple’s policies. Multiple tabs, auto complete URLs from the web, and quicker sharing features make it a good choice over Safari.
Asana: The mobile application isn’t great (too slow, no offline caching, no fast input for new tasks, seems to still use web views) but I love the web version so I need the todo list data on the go.
Hipmunk: Search for flights without seeing strictly worse flights (longer flights or for more money are hidden from results). The web version is better mostly because the airlines’ websites are unusable on mobile. Still great in a pinch.
Cloud Magic: Haven’t played with this too much yet but my first few searches across gmail, dropbox and gdocs produced good results. I have a lot of documents and messages stored in the cloud so there has got to be a single place to search across them. Open to other ideas here.
Venmo: Easiest way to send money to other people for free (with a debit or bank account attached). They’ve cluttered with odd sharing mechanisms which I am sure has made it stickier but they need a UI refresh to make paying people super super fast and efficient.
TravelNerd Airports: Nice data about what is around at your airport (restaurants in the terminal kinda stuff).
SeatGeek: An easy way to search for concert and sports tickets across the multiple ticket resellers.
Mail: I’ve tried every application for standard email and they all have a critical flaw: (1) Gmail app is one account, battery hog, and is slow, (2) Sparrow got slow and acquired, (3) still waiting to test Mailbox, did I miss anything else. Apple Mail is fast and multi inbox but search is horrible. Waiting on someone to solve this.
iA Writer: Distraction free writing and a mode where it highlights on your current sentence. Just a clean way to bust out some text. Syncs across devices with Dropbox or iCloud (I use dropbox) and has a Mac desktop application too. Not free.
Others that don’t need explanation: (Dropbox, Facebook, Twitter, Skype, YouTube, Yelp, OpenTable, Amazon, LinkedIn)
Many large (and small) companies ask employees to write self evaluations as part of its performance review. Each time management communicates a process broadly, it’s especially important to evaluate how it will affect people and the company from an operational, incentive, emotional, and organizational perspective. It’s not enough for the idea to generally seem positive, it has to have a goal, a purpose, an intention, and a plan— a self evaluation seems so thoughtful in theory; how could it go wrong?
Most review processes take the following form: HR department communicates the yearly performance review process, self evaluations are embedded in the multi week or multi month schedule, there is followup on how and where to write it, there are reminders, managers need to hound their team, some employees finish them, the review goes into the ether, nothing is heard from after.
Even the proper execution, self-evaluations are inherently flawed. What’s wrong?
- Inverse rankings: Often (almost always?) the best people are the most self-critical and will rank themselves on any scale lower than their non self-aware colleagues. I’ve found that self evaluation ranks are completely inverted. It’s hard to imagine another system that seems so straightforward and blessed by management theory experts that produces a inverse relationship to the truth. Ironically, this might be the process’ best asset as you can simply do 1/X to get the correct rankings.
- Part of compensation process: Self evaluations are often timed and included as an input to compensation review. While they might actually not be part of management’s judgment criteria, people naturally will think that their responses will factor into their salary or bonus changes. Anytime you directly tie an action to compensation, you will skew the behavior and turn the process into a game theory problem. Employees won’t give a true thoughtful self reflection; they will be incentivized to write responses that they think will lead to higher monetary outcomes.
- Review disappears: I’ve never heard of a follow up to an employee’s self evaluation. Low sample size but the systemic issue is that the reviews are operated and stored with the HR team and direct managers do not feel ownership and are not empowered to follow up. Self evaluations are in a murky private to you open to HR nebulous space. Employees believe they are either ignored or unsure of its use.
- Managers undermine the process: Since the evaluations are part of a multistage behemoth review process and are communicated top down and out of the blue, managers are basically as unaware of the goal and are as ill prepared as their direct reports. Managers, especially weak ones, will want to side with the feelings of their team and might opening mock the process or attempt to shield their staff from the perceived bureaucracy.
- Poor software or no software: Self explanatory. There is little employee confidence when the HR team attempts to use unpolished tools, poorly created Google surveys, tons of paper, etc…
- Faceless HR department: Would you be comfortable writing an intimate self evaluation process and blindly send it to a team you’ve never met?
- Fixed weights, custom drop downs, and scores: Out of 5, how well did you work with other team members and, out of 100%, what percent is that important to your job? Make sure it sums to 100%! Do you consider yourself (1) self starter, (2) team player, etc…
- Requires constant reminding and vague consequences: HR teams notice that there is slower than expected response to the self evaluations and then has to communicate to managers the percent of his or her team that has submitted. A vague carrot or stick might be used to coax managers to get their teams to comply and the same is done to their teams. A thoughtful process for people’s own benefit should require this.
Things can go off the rails so quickly when a plan isn’t interrogated from every angle. Many of these issues can be avoided but it starts with a straightforward but challenging question: What is the goal? To me, the goal of a self evaluation is to encourage people to be more self-aware, self-critical, and find ways to improve their performance and happiness. It is not a way for management to evaluate people, not part of any compensation or role decisions, not part of a performance review process, and not mandated.
Ideas for solution
- Communicate self-aware cultures: The act of evaluating your own performance and behaviors is an important tenet of the company culture. The company evaluates itself, executives pay attention to their own actions, and they reward people who improve based on being self-critical. The day to day environment has to reward, or at least not punish, people who thoughtfully fail, discuss their shortcomings, and ask for help. Only then would a self evaluation process be relevant and appropriate.
- Avoid single point top down communication from non executives: Each manager, along side of HR, should communicate that the skills displayed in being able to do a self evaluation in any format are part of how people advance at the company. They could provide examples of different forms that have been successful. Remember that since our goal is to encourage the reflective behavior, the form can just a matter of serialization.
- Optional: Forcing people to be try to be self-critical seems like a nonstarter. Encourage, train, but don’t enforce.
- Can be private: A self evaluation can be in any form and also be kept private. One could send it to a manager or it can just go into trash can. Since we’ve clarified that these are not part of the review process it should not skew behavior.
- Training: Help members of the team learn the skills and forms that being self-critical can take. What questions should you ask yourself? How should it be materialized?
- Decide the goal up front: Are you trying to get employees to think about their work, their successes, or areas they need help? Be serious about why you’re asking people to do things and explain it to them.
- Follow up: Managers must follow up, come up plans, goals, checklists, etc… These techniques are harder to implement than their bland, one size fits all counter part. It requires thoughtful and careful individual managers and trust from the business that the employee-manager relationship can address performance and behavior successes and struggles along side the official HR team.
While it’s harder and more subtle, it’s the right struggle and one that with iteration and communication has a more likely chance of achieving the goal. At least it will waste less time.
Some of these apply to small companies, some to large, some to all.
- Start on time
- Give an agenda
- Have multiple people speaker
- Have a theme
- Make it cute
- Contest with random winners that aren’t executives
- Refer to people by first name but also give background
- Ensure that everyone walks away knowing one new thing
- Have it on day where people don’t mind staying late
- Practice the technology (projector, video, sound, dial in, etc)
- Mute the line (if you don’t know how to do this, just give up)
- Special guests
- Music while people wait
- Put anyone on the spot
- No inside jokes
- No elaborate use of technology to foster involvement
- Don’t bring up prior events (good or bad) unless you have new information
- No awards
- Talk uninterrupted then ask for questions
- Talk about the past for anything other than context
- Reuse slides, have tiny font, unpolished graphics
- Offend people, be racy, think it’s an old man’s club, assume people have stock, assume people are all on the same compensation plan, segment groups by name
- Assume that people know the executives by first name
How you know it’s going well:
- Laptops away
- People hang out after
- Questions are asked, questions change week to week
More ideas: http://www.quora.com/All-Hands-Meetings. Tactical ideas have to be written down.
Randomness and serendipity
Forcing yourself to find experiences outside of your normal routine feels critical to being a well rounded human. From a professional and mental health perspective, meeting new people, being exposed to alternative ideas, appreciating the differences between cultures, observing the needs of others can lead to happiness and new ideas. Randomness and serendipity invite new worlds and life changing decisions. New industries and disruptive services are birthed from unique domain experts paired with advanced general purpose technologists; the unpredictable spark may be the by chance encounter, the yes to coffee, the silence to listen, and the let’s try it. Forget the work talk— variety of experiences and people makes me happy.
- Read more books (history, fiction, etc…)
- Travel (internationally, local, no hotels)
- Walking new neighborhoods
- Not wearing headphones
- Waiting in line
- Random online stumbles
- Movies, theater, radio, museums, photography
- Public transportation
- A positive, fearless attitude to the unknown
- Asking questions
- Farmers markets
- Showing up early, staying late
How do you increase the likelihood of these encounters? How do you maintain a healthy balance between your normal and the new?
The truth and the lie
Prospective employees, co-founders, investors, friends, and loved ones, they each want to be believe the rational and the irrational— the truth and the lie (maybe better called the “tale”). Startups, being statistically irrational for likely short term market or financial success, are fraught with moments of having to believe the irrational. The story of where we came from, why we’re here, and where we’re going can be and are often oversized.
There are other moments, some private, some open, where the truth, often smaller than the tale, is needed. Personal growth, new skills, community impact, confidence, independence, can all be reenforced when the tale feels so much larger than the current state of progress; something needs to give you structure when the cloud of unknown seems too murky as you try to foresee what’s next.
Great entrepreneurs, and leaders at all levels, must communicate the ever changing journey from truth to tale, while growing and evolving both at increasing rates. You always want to chase the sky over the horizon but need appreciate the ground along the way.
There’s data, there’s data, and then there’s data
We had a saying on my former team at comScore: there’s data, data, (pause) and then there’s data.
As you’ve likely too frequently read, there is more data being created and collected today than ever before. New data streams are being generated by modern businesses, governments, hobbyists, devices, etc… It’s often reported as the panacea to solve problems and a go to way to unlock new opportunities. The abundance of new data is correlated, if not caused by, the massive reduction in storage cost on both an absolute and relative basis. Moreover, storage and access can dynamically change with both planned and unplanned usage. Early stage technology companies often have a majority of their expenditure allotted to salary (labor with a capital L) rather than hardware (capital a capital K). Large companies can have major data related costs in hardware, licenses, and people though hopefully have reasons to invest given market success. For both large and small companies, there is affordable options to capture and store all the data within reach even prior to a known way to make sense of it or make money from it. Storing everything you can is treated like a no brainer.
Fine, granted, so what can we do with it? Well, there’s data, data, (pause) and then there’s data. Spoiler, there is a fourth level of data too.
Data level 1: Existence
- What to capture?
- How to implement measurement and storage?
Data level 2: Availability
- How to access?
- How to visualize?
Data level 3: Trust
- How to make decisions based on data?
- How to become a data driven culture?
Data level 4: Decision
- How to automate decision making?
- How to create data driven products?
I’ve heard some people map this to information -> data -> insight -> knowledge. This is bite sized, vague, and devoid of practical implication; it’s a I-know-it-when-I-see-it segmentation. Here is an attempt to walkthrough how to think about specific decisions you’ll encounter as you try to infuse data into your company’s operation, product, and psyche.
This will focus on broader operational decisions and motivation rather than specific technical systems. It also largely ignores the specific engineering challenges related to long term storage and serving data at web scale.
In the technology sector, it seems that only the upper echelon of large technology companies and promising, engineering focused upstarts can attract and afford the diverse technical, operational, and scientific talent necessary to answer the above questions.
I’ve ignore many related topics so just take this for what you will. If you’re passionate and can lead me to ways to make this easier, please send me a note. I think data and its applications will be the raw materials of the next great businesses and for all of our advancements, we’re still clunking our way through the basics.
The first level of data is merely creating and capturing it correctly. You’ve chosen to log something, you’ve implemented the tracking, you’ve piped it to homegrown (lots of work) or third party analytic systems, and you’ve verified it’s both consistent and complete. None of these tasks are trivial; they often require multiple people, iteration, debugging, etc… In the web space, you can go a long way by instrumenting client side code (what the user actually sees in browser) using excellent off the shelf tools like Mixpanel, KissMetrix, Google Analytics, ChartBeat, etc… This approach still requires front end modifications, testing, diligence to maintain, up front time for learning their systems, and some medium term lock in to their policies. You still need to do validation and common sense sniff testing to ensure you’re getting the results you’d expect, especially if you do anything even slightly custom.
Measuring server side code or other backend systems (the fun part where you application performs) is often performed by logging- your code writes out some flat lines of text or formatted key-value pairs (JSON, XML, etc.). Most business executives think this type of logging should come “for free” when systems are built but there is often complex work to create and capture relevant data.
This requires a level of precision not typically found in day to day non-engineering life. Even highly skilled analysts, big data distributed algorithm gurus, and Ph.D. data scientists are rarely equipped to design what to log and how to log it. It’s a bit of science and art. There are tradeoffs for performance, data size, correctness, etc… Many of these tradeoffs require thinking through how the data will be queried which means predicting usage by others (not an easy task). Engineers may approach this from a code coverage perspective: “Are we logging errors? Is code executing in a performant way? How early can we tell there is a functional problem? Are the machines operating normally?” While critical and necessary, it is not sufficient. We need to also measure if the system is achieving its goal: “Are the current outputs or behaviors correct and/or normal? Are users using the system in successful way? Is the data being generate useful?” These questions require much more thoughtful definition and are inherently subjective. You need to interpret how code impacts people, businesses, and other systems. You can successful log errors, keep the machines healthy, maintain your uptime, beat your SLA requirements, and still produce garbage data? Do you want to know that ASAP or when people start complaining downstream…
Concrete example: At Hyperpublic, we indexed lots of data about local businesses, places, and venues from publicly available sources. We were building, and the team continues to build at Groupon, scalable systems for collecting this data, normalizing it, and determining the most likely accurate information. Let’s imagine we’re interested in the physical address of the business: it’s not enough to instrument application code to alert on errors, we need to monitor how well the system is determining a place’s likely street address. Yeah, the machines are on and the processes are running, but is it producing good results? Should people using this data be happy?
One helpful way to get started is to pick one, and only one, measure of a data stream’s validity. Picking one metric that means something to the team can be the driving motivation to follow through the project from beginning to end (Kissmetrics blog has a nice detailed post on some ideas per business type). It’s best, though not required, if this measure can (1) be computed independently from other systems, (2) operate on one record at a time, (3) be stateless, (4) performed computationally trivially, (5) improves the accuracy of the test over time, and (6) have tangible meaning to non-engineers and non-stats people: i.e. normal people. This means that your metrics can be performed on streams of incoming data, can be distributed over multiple threads, process, and/or machines, doesn’t impact application performance, creates new understanding of expected results over time, and can be described to everyone in the company. If it fails any of these needs, you may have to overcome more complex engineering and insight challenges but that’s where the creativity and fun comes in.
Designing these metrics is the fascinating intersection of engineering, statistics, and business insight. Are you looking for a massive abrupt shift, a slow change over time, or an individual data anomaly? Being aware of how you’ll evaluate the summary statistics will impact your choice in how you measure and design the system.
That’s a lot of work, and we’re still at data level one. If your data isn’t well structured, you’re in a whole other boat.
Data level two.
Ok. So now you’ve chosen what to measure, next up is convincing the team, or yourself, that it’s important to integrate the tracking. This can become a major endeavor that can rabbit hole its way into a long term project with no clear early wins. Do not bite off too much at first. Pick one thing, get it working, get it on a graph, get that graph on the wall, and high five. Yes, you will make some short term decisions that will likely require rewriting down the line. Yes, you will build some short term systems that are single purpose, don’t scale to new sources, don’t allow for arbitrary analytic access, but this is the only way I know how to get anything done. I don’t always do a good job with it because it can be so damn fun to plan and draw data flow diagrams (seriously one of my favorite things to do). Resist the urge. Use the open source tools, steal the front-end view from your neighbor, and just get that metric on the wall. You’ll feel better.
Data level 3. If you’ve made it this far, the data is flowing… Can you query it? Can you, with confidence, make decisions based on it? Can you ask someone else at the company what the state of that monitor is? Is it in your daily workflow? Does everyone trust it? Can the CEO read it? Is there any ambiguity? This is the softer, and harder, side of data. It always have caveats, coverage issues, and is susceptible to misinterpretation.
Your instinct might be to create wikis though they have very low likelihood of improving the situation. This step does not come overnight. You need to create a trusting relationship between the data and you, your team, and your company. Like all good relationships it takes time, attention, frequent interaction, retrospection, and occasionally intervention. Once you reach a healthy level of trust, data will become invaluable. Everyone will want access, teams that didn’t see the value earlier will want to participate, and data will have a voice when decisions are made. Now you might need to rebuild your systems to handle the scale of new use cases, uptime requirements, data volume, storage needs, privacy requirements, access controls, retention policies, ad hoc vs. production schedules, concurrency, asynchronous collection, better viewing tools, alarms, sessionization, long term reporting, back up, etc… This just became a real asset and requires commitment.
Data level 4. This is the stage that’s talked about the most— data as a feature. It’s what powers product recommendations, search engines, news feeds, ad targeting, etc… There is statistical, testing, and production engineering focused on servicing data needs in this area but we’ll leave that for another post. This is the promised land but is a ways off from where most companies are…
This was a very high level and likely too wishy washy view but one that I hope highlights that realities of creating a data driven culture that is overlooked in the typical how big is your big data discussion. If you’re good at this stuff, please let me know.
People come to the Apple Store for the experience and they’re willing to pay a premium for that. There are lots of components to that experience, but maybe the most important—and this is something that can translate to any retailer—is that the staff isn’t focused on selling stuff. It’s focused on building relationships and trying to make people’s lives better. - Ron Johnson