Through a posting of Roel I came across Rick Klau again, someone who like me was blogging about knowledge management in the early ’00s. These days his writing is on Medium it seems.
Browsing through his latest posts, I came across this one about homebrew contact management.
Contact management is one area where until now I mostly stayed away from automating anything.
First and foremost because of the by definition poor initial data quality that you use to set it up (I still have 11 yr old contact info on my phone because it is hard to delete, and then gets put back due to some odd feedback loop in syncing).
Second, because of the risk of instrumentalising the relationships to others, instead of interacting for its own sake.
Third, because most systems I encountered depend on letting all your mail etc flow through it, which is a type of centralisation / single point of failure I want to avoid.
There’s much in Rick’s post to like (even though I doubt I’d want to shell out $1k/yr to do the same), and there are things in there I definitely think useful. He’s right when he says that being able to have a better overview of your network in terms of gender, location, diversity, background etc. is valuable. Not just in terms of contacts, but in terms of information filtering when you follow your contacts in several platforms etc.
Bookmarked to come up with an experiment. Timely also because I just decided to create a simple tool for my company as well, to start mapping stakeholders we encounter. In Copenhagen last September I noticed someone using a 4 question page on her phone to quickly capture she met me, the context and my organisation. When I asked she said it was to have an overview of the types of organisations and roles of people she encountered in her work, building a map as it were of the ecosystem. Definitely something I see the use of.
Handshakes and conversations is what I’m interested in, not marketing instruments. Image Handshake by Elisha Project, license CC BY SA
I’ve held for a long time that whenever someone says “we’d like to hire women but we don’t know any” or “we really want women as speakers on our event but we don’t know any and if we do they say no”, it is really down to the lack of quality and balance in their network of contacts. When I organised international conferences myself, with our team we made sure to invite speakers while conscious of the lopsidedness of our own networks, overcompensating in our invitations to get a result closer to a 50/50 balance. Now that my company is hiring new people every now and then, that too is an opportunity to counteract such imbalance.
Last week I wrote about ‘homebrew CRM‘, in which I mentioned Rick Klau’s post on his contact management routines. One element that jumped out when I was reading his post was that he had taken a look at his contact lists to see how the men/women ratio was in his network. There’s nothing in LinkedIn that let’s you explore your contact list as a single data set. It’s only a rolodex still, no way to visualise the data in that list in any way (e.g. geographic or sectoral distribution, or other cross sections of the list). Rick mentioned he had downloaded all his LinkedIn data and all his Twitter data, and then used that data export to work on. I requested the same data from LinkedIn and Twitter.
It turns out that LinkedIn’s export contains a list of contact names (but not the link to their profiles, as that isn’t ‘your data’), and a key piece of information they normally don’t show you: the date you connected. (Interestingly LinkedIn offers you nothing to record the context and reason you connected. The Xing-platform, heavily used in Germany, does do that, and I find it very useful)
Having names and dates, I manually indicated someone’s gender, and then used the dates for basic insights into how my recorded network developed over time. (Typing this I realise I still have the export from Facebook when I deleted my original account 2 years ago, and I could do the same there)
For now I looked at two measures: the balance between women and men in contacts I added each year, and the balance between women and men in the total number of contacts each year. Currently I have some 2150 contacts, of which some 600 are women, for a percentage of 27%. That is significantly lower than I had intuited. I think such overestimation is a known effect.
Looked at per year for the contacts added that year, the balance over time has improved from 10% in 2003, to between a third and 40% in the last handful of years. That last number is in line with the overall percentage I had intuited, so apparently I am using my perception of recent years as the estimate for the entire period. That low 2003 starting percentage has a lot to do I think with the general imbalance of the early adopter crowd that came into LinkedIn when they launched in May 2003 (I joined in June ’03) and the low number of people I connected to those first months on the platform (11 in 6 months).
Getting closer to a 50/50 balance on LinkedIn isn’t completely within my control I realise (unlike in my feed reading), as it also depends on who I actually meet in my work, and each working environment has its own existing gender distribution. It is also not completely outside my control. There is agency in new situations and contexts, such as whom I seek out for conversation when participating in an event. Yet, getting to a 50/50 balance for the total would mean connecting only to women for a few years, adding about a 1000 new contacts that way. History does keep one back clearly.
cummulative per year
new contacts added per year
A few days ago I took a look at my LinkedIn data, and realised while writing it that I exported my Facebook data in the fall of 2017 when I first strongly reduced and then later closed and deleted my original October 2006 account (I do keep a new account with limited interaction and much fewer contacts). The Facebook data also has a list of contacts with the date they became a contact.
From that export I therefore created the same data I did for LinkedIn: the number of added contacts per year and its gender balance, and the cumulative number of contacts and its gender balance. This in response to Rick Klau’s description of his ‘do-it-yourself contact management‘ Between 1 October 2006 and 30 October 2017 I added some 650 people on FB, of which 161 women (25%)
Those numbers are even more out of balance than with LinkedIn, although in recent years it improved in much the same way per year as on LinkedIn, though it comes out slightly below LinkedIn for the total. I suspect for Facebook a social aspect is in play more than on LinkedIn: for a larger social distance I suspect it is socially more likely I’d add a male contact. To test that I would need to arrange the contacts by my perceived social distance, which is an interesting experiment for another moment.
cummulative per year
new contacts added per year
First in Peter’s favourites from his feedreader, then from Matt Webb’s feed directly, which both showed up right beneath eachother when I opened my feedreader this morning, I read Personal Software vs Factory Produced Software.
In that posting Matt points to Rev Dan Catt’s recent week notes, in which he describes the types of tools he makes for himself. Like Matt I love this kind of stuff. I have some small tools for myself like that, and it is the primary reason I have been running a local webserver on my laptop: it allows me to do anything I could do online right on my laptop, as home cooking. Transposing code snippets into safe HTML output for instance. Or converting bank statements into something I can import in my accounting spreadsheet. Those are however somewhat of a mechanical nature. They’re by me, but not about me. And that is the qualitative difference specifically of the letter/cards tracking tool described in Rev Dan Catt’s post.
That is more akin to what I am trying to slowly build for myself since forever. Something that closely follows my own routines and process, and guides me along. Not just as a reference, like my notes or wiki, or as a guide like my todo-lists and weekly overviews. But something that welcomes me in the morning by starting me on my morning routine “Shall I read some feeds first, or shall I start with a brief review of today’s agenda.” and nudges me kindly “it’s been 15mins, shall I continue with …?”, or “shall I review …, before it becomes urgent next week?”. A coach and PA rolled into one, that is bascially me, scripted, I suppose. I’ve always been an avid note taker and lists keeper, even way before I started using computers in 1983. Those lists weren’t always very kind I realised in 2016, it became more a musts/shoulds thing than mights/coulds. Too harsh on myself, which reduces its effectiveness (not just to 0 at times, but an active hindrance causing ineffectiveness). I wanted a kinder thing, a personal operating system of sorts. Rev Dan Scott’s correspondence tool feels like that. I reminds me of what Rick Klau described earlier about his contacts ‘management’, although that stays closer to the mechanical, the less personal I feel, and skirts closer to the point where it feels inpersonal (or rather it challenges the assumption ‘if you don’t know it yourself and keep a list it’s not authentic’ more).
Building personalised tools, that are synchronised with the personality and routines of the person using it, not as an add-on (you can add your own filter rules to our e-mail client!), but as its core design, is mostly unexplored terrain I think. Because from a business perspective it doesn’t obviously “scale”, so no unicorn potential. That sort of generic scaling is unneeded anyway I think, and there is a very much available other path for scaling. Through the invisible hand of networks, where solutions and examples are replicated and tweaked across contexts, people and groups. That way lie the tools that are smaller than us, and therefore really provide agency.
It’s also why I think the title of Matt’s post Personal Software versus Factory Produced Software is a false dilemma. It’s not just a choice between personal and mass, between n=1 and statistics. There is a level in between, which is also where the complexity lives that makes us search for new tools in the first place: the level of you and your immediate context of relationships and things relevant to them. It’s the place where the thinking behind IndieWeb extends to all technology and methods. It’s where federation of tools live, and why I think you should run personal instances of tools that federate, not join someone else’s server, unless it is a pre-existing group launching a server and adopting it as their collective hang-out. Running personal or group tools, that can talk to others if you want it to and are potentially more valuable when connected to others, that have the network effect built in as an option.