Category Archives: competitive intelligence

DigitalArtsNation.ca launched!

Today, we’ve launched digitalartsnation.ca, the website for Making Tomorrow Better: Taking Digital Action in the Performing Arts. This initiative received significant funding from the Canada Council for the Arts’ Digital Strategy Fund in spring of 2019. The nation-wide partnership led by the Atlantic Presenters Association includes the Manitoba Arts Network, BC Touring Council, Island Mountain Arts/Northern Exposure, Yukon Arts Centre / N3 and the Yellowknife Arts & Cultural Centre.

logo Making Tomorrow Better Taking Digital  Action in the Performing Arts

Of note: most of the participants in the face-to-face workshops live on the edges of the country. therefore we tailor content to suit the realities, including slower internet connectivity,  of rural and remote communities across Canada. Because what works there, will work in urban centres, too.

This national initiative brings practical digital know-how to participants across Canada, through custom workshops, online how-to tutorials and information-sharing

These workshops are designed to help participants speak digital with confidence – that is, we will demystify and discuss the digital realm in plain English – and quickly become competent participants in arts sector conversations about leading digital tools, emerging digital innovations, and new digital business models.

Workshops are led by Inga Petri, Strategic Moves, or Tammy Lee, Culture Creates.

Watch our upcoming workshops page and see where we are headed next!

How intelligent is AI today?

I recently attended a workshop by Arts Impact AI, which is undertaking conversations on AI across Canada. I discovered quickly that my expectation of what Artificial Intelligence (AI) is, wasn’t quite in the right place for the conversation at hand. I expected the discussion to centre around intelligent machines thinking and working similar to humans. Where attributes like self-learning or the ability to intelligently change its programming based on new input would be explored.

Algorithm Making

We spent the morning considering algorithms capable of rapidly analyzing vast amounts of data. An intuitive example came in the form of a group exercise where group 1 developed an algorithm (five characteristics based on a set of 12 images of convicted criminals) to identify the most likely criminal in a crowd, group 2 – the computer – applied the algorithm and group 3 – the humans – were tasked to simply identify the criminal without an algorithm. My colleagues in group 1 –  which was made up of people from diverse backgrounds and ethnicities who live on the traditional territories of self-governing First Nations in the Yukon (and yes, that might have mattered to our decision-making) – opted to select criteria that did not include racial stereotypes. Needless to say, we broke the machine.

Each group had serious struggles with the ethical implications of their group’s role. This was the point, of course: do the designers of algorithms simply reinforce the stereotypes based on a highly biased judicial system that disproportionately affects Indigenous people and people of colour, and often men that are visibly part of these groups; or do they write an algorithm that does not fall into those stereotypes but focuses on other aspects.

Big Data Analysis

In my way of thinking this kind of AI application lives in the realm of big data analysis. While I imagined AI to feel unfamiliar and new, this felt extremely familiar to me: As a market researcher, I have followed for years work on “big data” analysis and how with the aid of faster computers our ability to analyze truly vast data sets has increased many fold. The biggest advantage, indeed, being speed that cannot be matched by a single human brain.

The AI application this group exercise mirrored is based on the analysis of a vast amount of data, e.g. 10,000+ photographs of convicted criminals, using computer facial recognition. This analysis identifies statistical probabilities for the parameters that were set.  Those probabilities are then used by humans to program an algorithm. That algorithm seeks to identify people in large crowds that match the analysis. By definition, this kind of analysis is looking to the past to inform the future; or in this case, to become the future.

Ethical Dilemma

The humans who build such algorithms  – which itself is void of AI self-learning or the acquisition and application of new information and capacity – determine their outcome.

When these humans do not apply a greater understanding, or an ethical lens (related to systemic impacts of oppression of certain groups in society, for instance) to the parameters analyzed in the first place, or to the resulting statistical probabilities, they are bound to create algorithms that reinforce the systemic biases evident in society.

In short, they may miss a lot of criminals and identify a lot of non-criminals. In so doing, they may also ensure that more of the same groups of people are pursued with the government’s righteous rigour, resulting in higher incarceration rates for these groups. Rather than discover what is real, it perpetuates a seriously biased reality that increasingly would disadvantage specific groups. The past literally becomes the future.

AI governance as data governance

This discussion of what algorithms are today centred on big data and what we can and should do with it was fascinating. Alas, it didn’t paint a picture for me of artificial intelligence in the sci-fi sense.

In any case, as a result of this data focus, the AI governance discussion was heavy on data governance, i.e. the collection, storage and use of personal data. Personal Information Privacy and Electronic Documents Act and  provincial laws govern information that is identifiable to an individual already. Canadian Anti Spam Legislation tries to combat spam and other electronic threats. There is a Do Not Call List to regulate how landlines can be used. These legislative tools tend to deal with a specific technology. This approach leaves much grey and blank space as companies explore and create more advanced technological innovations.  Simply put, technology changes more rapidly than laws.

In the end I feel it is this conundrum that AI governance should address – to move away from regulating one specific technology at a time to contemplate the notion of privacy and social licence we wish to adopt in our society.

Definitions of Artificial Intelligence

Artificial intelligence (AI) is an area of computer science that emphasizes the creation of intelligent machines that work and react like humans.

Some of the activities computers with artificial intelligence are designed for include:

  • – Speech recognition
  • – Learning
  • – Planning
  • – Problem solving

[Source: Technopedia]

4 Types of AI

  1. Reactive machines – e.g. Deep Blue chess playing machine
    • Reactive machines have no concept of the world and therefore cannot function beyond the simple tasks for which they are programmed.
  2. Limited memory – e.g. autonomous vehicles
    •  Limited memory builds on observational data in conjunction with pre-programmed data the machines already contain
  3. Theory of mind – e.g. current voice assistants are an incomplete early version
    • decision-making ability equal to the extent of a human mind, but by machines
  4. Self-awareness -so far only exists in the movies
    • Self-aware AI involves machines that have human-level consciousness.

Source: G2

Cross-posted on https://digitalartsnation.ca

Digital Strategy Fund: Funded Projects 2017 – 2019

Canada Council for the Arts announced its unique Digital Strategy Fund (DSF) in March 2017 with a sense of urgency: “The fund is part of a catch-up movement for the vast majority of the arts sector, which is at risk of being less and less visible and less supported by citizens (…)” As a strategic fund, it is time-limited and was to operate from 2017 to 2021. The Digital Strategy Fund is worth $88.5 million.

UPDATE August 12, 2019

Canada Council for the Arts’ Strategy and Public Affairs supplied to me new tables on August 9, 2019. My initial analysis was based on Canada Council’s grants database information. That public information does not include the amounts committed by Council to multi-phase projects as those funds will be released based on interim project report. The different between the Grants data base as of August 9, 2019 and the actual allocated pending reports is just over $7 million, i.e. $36 million as opposed to close to 29 million. Another difference was in the year to which projects were allocated, i.e. many of the projects marked 2019 actually belong to the 2018-2019 fiscal year and are now marked 2018.The basic point of the analysis remains: less than half the available fund have been allocated so far leaving significant opportunity space for new applications to the fund.

Tables below are updated using the new data supplied by Council.   

I hope it will illuminate where funding has gone and help see where the digital opportunities spaces might lie for the upcoming September 18, 2019 deadline for the next full round of funding.

Canada Council for the Arts Digital Strategy Fund 2017 to 2019

Table1 Digital Strategy Fund 2017 to 2019

In total, the DSF has spent $36 million for 352 projects for an average of $102,961 per project. (*IMPORTANT NOTE: The total number of projects funded is 352 over this period, however, multi-year projects are counted in each of the fiscal years in which funding is awarded.) 2018 saw nearly seven times as many projects funded, resulting in a quadrupling of funding allocated. The average funding in 2018 is substantially lower because it includes a round of funding for core funding recipients that maxed out at $50,000.

$36 million represents only 40% of the total ear-marked funding.  It is clear: there is tremendous opportunity to obtain funds for bold digital experimentation in and a great deal of learning about the digital realm  with the remaining $52 million over the next two years.

Canada Council for the Arts Digital Strategy Fund - Four Funding Streams

Table 2 DSF Funding Funding Streams

During these first two years, Digital Literacy projects have 25% of all funding allocated.  Public Access and Citizen Engagement stream received 29% of funds – representing 16% of projects, while the Transformation of Organizational Models received about 26% of all funding for close to 10% of all projects.  This assumes all multi-phase projects will proceed beyond their initial phases and the allocated funds will be disbursed. The Special digital projects for core grant recipients makes up about one fifth of the funds spent, but half of the projects. The multi-phase projects while few in number represent a very significant investment of the life of the projects in particular when they meet their go/no go metrics positively.

In a sector that by and large is lagging in the adoption of contemporary and leading digital tools and methods, these figures paint an encouraging picture: Not only are arts organizations embarking on becoming well versed in the use of digital tools but a considerable number are working toward producing, marketing and distributing participatory and receptive arts experiences by experimenting with and leveraging the tools and methods of the digital realm; and 34 projects representing $9.5 million ($5.7 ,million of funds have been released pending multi-phase project go decisions for later phases) are looking at what digital transformation might look like for their organizations and sectors.

These projects are predicated on partnerships and generating significant benefit for more than the lead applicant. As such seeing a segment of the arts and culture sector embracing this opportunity to obtain risk capital for strategic organizational model and business model experimentation in the digital world is encouraging.

Canada has become highly urbanized, with about 17 million Canadians living in the six largest urban centres, and more than 80% living in urban and sub-urban areas of Canada. This begged the question about the geographic distribution of funds so far.

Canada Council for the Arts Digital Strategy Fund Cities vs the Rest of Canada

Digital Strategy Fund Cities vs the Rest of Canada 2017 – 2019

The six largest urban centres across Canada have received 68% of all funding even though their general population comprises about about 47%. This suggests that there is a greater concentration of organizations and activities in the digital realm in the largest cities. Nonetheless, $11.5 million have gone to cities under 1 million as well as smaller jurisdictions including a few in rural and remote places. The average level of funding per project is on par when we exclude the special projects at about $103,000. Still, one of the promises (opportunities, challenges) of the digital realm is that it might create a more level playing field for geographically disadvantaged and systematically excluded places and people. There is a need to explore how smaller communities can build the capacity needed to access more of this funding. 

Canada Council for the Arts Digital Strategy Fund 2017-2019, Regions

Digital Strategy Fund 2017-2019, Regions

Further analysis shows that every region in the country has benefited from the Digital Strategy Fund; and it matches quite well to the size of population, with only the three Prairie provinces under-performing significantly by the measure of general population.

Canada Council for the Arts Digital Strategy Fund 2017 to 2019, Provinces and Territories

Table5 Digital Strategy Fund 2017 to 2019, Provinces and Territories

Perhaps not surprising given their population base or remoteness, the Northern Territories and PEI  have received funding for only 1 to 2 projects each so far. While on a population basis this would be deemed adequate, it does not reflect the depth and breadth of the arts and cultural communities.

In my  work with arts and cultural organizations in every province and territory in Canada over this decade, I have seen exceptional arts communities in unlikely places and without exception they have an interest in staking a claim in the digital realm. I expect and hope to see more winning proposals from strong local arts and culture sectors in Nunavut and Yukon as well as Vancouver and Gulf Islands, BC Interior, NWT, Newfoundland, rural Maritimes  as well as cottage country in Ontario.

Bottom line: with 60% of the ear-marked funding envelope not yet spent, the time is ripe for a plethora of proposals for the September 18, 2019 deadline. Plus there is money available for Digital Literacy projects under $50,000 to succeed any time you need them – indeed, you can apply as often as you need under this component!

Let’s get on it! Let’s talk!

Notes: I collated this spreadsheet DSF_2017to2020_Aug2019 from the data points on Canada Council for the Arts’ proactive disclosure website. It represents 337 projects and is based on a data pull on August 2, 2019.

The funding database for DSF does not specify the artistic disciplines or whether it belongs to an equity-seeking group

The three funding streams allocate either up $250,000 for single phase or $500,000 for multi-phase projects, and up to 85% of total eligible costs for a new project or 50% to refine or optimize an existing one. By any measure this is a significant and unique investment in the arts and culture sector in Canada. New in 2018 was that Digital Literacy projects of up to $50,000 can be submitted any time to be approved internally at Canada Council within a few weeks, ie without convening an expert jury. Also new was that the expectations around having a partnership lead these projects has been loosened to specify that it must benefit a wider group.

Three rounds of funding have taken place: the first closed in fall 2017 with funded projects announced in April 2018, the second one closed in fall 2018 with projects announced in April 2019, and the third one targeting organizations that receive core funding from Council was published in summer 2019.

 

Artistic Risk and Branding

Creating a strategic framework to achieve value innovation  means we need to ask basic questions as if they were brand new. For example, what does “taking artistic risks” mean from an audience perspective?

The answer is that “it depends”: Each audience member determines “risk” using a slew of criteria to figure out under what circumstances it might be worthwhile to not actually enjoy a performance that one paid for and made time to attend.

Personally, I attend several performing arts on subscription – the ultimate commitment much of the performing arts still relies on. I have different expectations from different art forms. In terms of classical music voluntary risk taking is limited to listenable music (I have little tolerance in the orchestral setting for dissonance). In contemporary dance, I look for the new and unexpected, as long as the dancers are top notch and indeed are dancing. In theatre, I like intellectual, thought-provoking work and I like a great deal of variety, too, including some great brassy entertainment that tells a great story. I also really like mash-ups that blur the boundaries of art forms by taking the best from each and creating something even greater. (Fela!, which I saw at Toronto’s Canon Theatre, is an extraordinary example of that.)

I have just established, in my singular experience at least, that it is possible within the same person to evaluate risks quite differently depending on the context.

The very idea of “artistic risk” is highly subjective. For instance, not all risky programming is innovative, and what’s perceived as a risk in one city may not be so risky in another. Risk is contextual not absolute.

Performing arts audiences are diverse in tastes, expectations, culture and background. Those who can afford tickets easily will evaluate risks differently from those who have to give up something else in their life in order to save up for tickets.

Effective branding is critical to success 

I propose that developing and living a strong, singular brand is the best way for creators and presenters of artistic experiences to help their audiences decide to give all manner of experiences a try and to invest their time and money.

The brand becomes the touch point, the guarantee of a thoughtful and respectful arts experience, whether or not it’s “entertaining”, “provoking”, “escape” or “stimulating”.

Robert LePage when receiving the Governor General’s Performing Arts Award recognizing his body of work was quoted about not wanting to be merely “international” but “universal.” (Watch the short NFB film here.)That is a quintessential brand statement, captured in a single word. It is awesome! It is a strong brand statement within which he can explore all manner of ideas in myriad ways; it’s not limiting but rather gives a meaningful contour to his work and aspiration.

He talked about his visual language of theatre evolving beyond the spoken word and to borrow from other forms of storytelling that are familiar for contemporary audiences – most important being film. From a brand point of view, that means he’s breaking free of the “traditional” bounds of one art form in order to bring his vision to life and to stay relevant. It’s an act of reinvention, which is requisite to maintaining brand relevance in the long-term.

Societies, communities, people, technology have been changing rapidly – socially, politically, environmentally, economically, (multi-)culturally. Every industry, every sector in society must change in relation to these external challenges. Those that will succeed are those that will bring audiences, customers, consumers along on the journey.

I propose that to define and embrace a comprehensive brand (not a logo, but a way of being), one relevant to audiences and stakeholders in your community, is the most efficient and effective way to connect the arts, artists and audiences to create success.

Imagine: creating a brand new genre of live music making today!

Yes, as if it was brand new. Where would you start? 

I would start with looking at my potential audiences and what they thrive on today. I would look at my community, its demographic make-up, its values, attitudes and beliefs and I would segment. I might identify those huge numbers of people who listen to music electronically, primarily using ear buds, irrespective of genre. I would examine deeply where they find their music, what they are listening to, how they listen to this music, when they listen to it, whether they share it with others and how, why they listen to their music, what music gives them, and what music gives them that nothing else in their lives does.

Then I would find out how they spend their days, how much time they spend being social and what they gain in their social interactions. I might see that there are grave pressures and stressors in people’s lives, and a wide range of worries and concerns that express themselves in various ways, including making people sick, feeling isolated and alone. I might think about how their current consumption of music via ear buds enhances these issues or alleviates them.

Then I might realize that the highest potential revenue is available in the 30 to 59 year age group – according to Statistics Canada data. I would use an existing geographic segmentation tool to understand demographics, values, attitudes and beliefs by postal codes, allowing me to see many dimensions of potential audiences.

I might determine that there are two different generations in this 30-year age span – Boomers and Gen Xers – who hold different generational values. I might decide that Gen Xers would be the sweet spot as they are less individualistic in orientation and I could foster and keep them as customers longer because they are younger. I would do this knowing that they tend to be more independent-minded even as they value communal spaces and social connections.

I would see that my target Gen Xers create, participate and engage in every dimension of life (socially, environmentally, politically, economically, artistically). I would see that they are sophisticated consumers who research, explore and sample online and by recommendation (both peer and paid recommenders). They are curious about new experiences and are excited to try out things they haven’t done before. I would see that they tend to look to be entertained in a friendly atmosphere rather than simply accepting others authority and doing as they are told without knowing why.

Then I would find out where this generation spends time and what their days, evenings and nights look like. Are they indoors in front of large screens or having family and social time, are they on the run using mobile devices as a primary interface while working hard, are they hanging out in coffee houses, bars and restaurants to get face-time, as they also chat and engage in social media to share with their wider community, are they in Yoga studios and fitness studios, spas and aesthetics shops where pampering is the order of the day and image is honed? Or do they work and worry about having enough money and resources to make ends meet? Different segments, micro-segments, would dominate in various activities and I might decide that I want to provide my solution – live orchestral classical music (ha!) – to all of them or some of them.

Then I might ask myself: how can I connect my brand new idea, never been seen before type of music making requiring perfect harmony among 40 to 100+ (!) musicians to these Gen Xers? How is my idea, that thrives on delicate sound (both in the highs and lows – qualities that are harder to appreciate and hear in compressed digital files), complex structure and intricate music making with a bewildering array of instruments, going to make these sophisticated, busy Gen Xers’ lives better, richer, more complete? What is the value Gen Xers would gain from such a formidable live experience? How is that value greater in comparison to other activities in their lives? How do I connect this live experience through online/mobile channels and make it irresistible? How will I secure true participation in the live music making?

Then I would decide what the business model is going to be, after all, getting that many musicians to play together will take considerable resources especially in the mid- to long-term. In essence, I would think about whether there can be economies of scale in my business model and what they are. For instance, I might realize that the live performance doesn’t scale well and I might search for ways to extend the live aspects to further monetize them. I might borrow from the playbook of other live events, whether its sports or pop and rock music.

I would look to other music experiences for inspiration, from the house concert to the stadium rock concerts. I would also look to the video game industry because it is highly participatory, the high-end spa experience because it does so well at pampering and getting me beyond my daily concerns, and the travel industry, both packaged and independent travel. And I’d think about styles of performance a lot.

This would eventually get me into the weeds of decision making: Would I put the musicians in a closed music making space, a concert hall, or would I put them outside or in community contexts? Would I have musicians be perfect technicians playing all the notes just so, or would I think about all that’s needed for an awesome performance experience for the audience? Would I ban the enthusiasm of my audience to the ends of long pieces, or would I encourage spontaneous outbursts of joy, delight, feedback? Would I dress musicians in black tails or would I allow their personalities to shine through with more than their hair styles? I would deeply consider the trade offs in each decision, talk to musicians and audiences and figure out how they would shape my brand.

Building such a bold idea from scratch would be awesomely exciting.

Finally, I would figure out how to build-in “creative destruction” mechanisms, so that the audience experience stays fresh and vibrant, rather than becoming narrowly defined by my initial magic formula. Everything tells me that there will be significant disruptive factors of all kinds, most of them outside my control, so that I might as well build in change and evolutionary leaps into the DNA.

Where’s the Blue Ocean for Live Performing Arts?

The past is not the best way to predict the future; especially when the context is highly dynamic, change is rapid, consumer behaviours, values and beliefs have shifted and commonly held internal beliefs (like the one about price elasticity) no longer apply (if they ever did: like the one about price elasticity).

I see the live performing arts in general at a crossroads in these changing circumstances: Which parts of the sector will adapt, which ones will become obsolete, which ones will grow, which ones shrink? What will success for the performing arts look like in the near- and mid-term? I hear about the dominant concerns being “audience development” and stability of direct government funding. As a strategist and marketer I think the dominant focus on these two concerns has not been producing the requisite breakthroughs in most cases.

In essence, I plan to think out loud about the value innovation that the performing arts sector in Canada could undertake to reap awesome rewards through creating uncontested – and valuable – market spaces. There are already examples of Blue Ocean creators in the performing arts: most notable may be billion dollar empires Cirque du Soleil and Apple. Yes, that Apple: Music has already been revolutionized by digital music distribution and most of that is revenue that goes to Apple. That may well speak to the power of owning the de facto ‘operating system.’

A Blue Ocean is a strategic construct reverse engineered by W. Chan Kim and Renée Mauborgne. It’s a strategy frame to make your present-day competition irrelevant, often by redefining what business you are in and the attendant changes that follow that understanding. Those don’t have to be thought of as global – they can be local or apply to a sector for that matter.

To play with these ideas relating to the performing arts, I’ll draw on my experiences and perspectives from the arenas of research, strategy and marketing. This no doubt will be a non-linear exploration; it will simply evolve as it goes … I hope it will become a conversation.

(first posted November 2011)

Many of these thoughts originated here during 2010 and 2011. They are as interesting to me today as they were then.

Economics of fear reloaded

Back in early 2009 I was struck by the incessant credit crisis coverage that had been going on since Lehman’s Brothers collapse in 2007, and before then if you had been paying attention to the sub-prime mortgage asset-backed securities issue. I thought it had to have impact on how people would behave in terms of consumption choices.

Economics of Fear and Sustainable buying practices

Now it’s late 2011, and we have just come through 5+ years of unending credit crisis, recessions and now debt crisis news coverage.

The coverage of “the markets” – those mysterious beyond-human-beings-making-decisions markets – is like a game show or maybe an endless cricket game, just a lot faster:  like hockey where the spectator never quite “sees” the puck but can infer it from the players motions.

The headlines are unhelpful at best to illuminate the issues – headlines are there to “sell papers”, or in online vernacular “secure eyeballs.” (It’s good to remember the motivations each industry has in its activities.)

Yesterday’s news of German Bond Auction not selling out is a prime example of disinformation moving faster than light (Neutrino pun intended): How many in the public who consume headlines know what a bond auction is, how it works and who the usual buyers are? If you read beyond the headlines you might learn a few other facts:

They come from the bottom of a Wall Street Journal article headlined: “German Bond Sale Spurs Worries”

  • “Germany had never tried to sell a 10-year bond that paid only 2% interest, and the historically low yields appeared to depress appetite among the traditional circle of buyers.”
  • “Germany sold 3.644 billion Euros at 1.98% average interest.”
  • “Germany traditionally auctions bonds, rather than operating a syndicate of primary dealers to place them with investors. The Finanzagentur, the government’s issuing agent, then gradually feeds the bonds it doesn’t sell into the secondary market. This system means that there is no pressure on banks to bid for the bonds or risk their relationship with the sovereign. Moreover, banks across the Continent are trying to reduce their holdings of sovereign bonds, or at least not take on extra exposure, Mr. Krautzberger said.”
  • Take a moment to check out the interactive feature in the article that shows how German bond yields have declined recently …

No doubt it sounds like the Finanzagentur miscalculated and underestimated the political sentiments and headlines that could follow if they did not sell out and the concerns they might raise.

Bringing it home I have two questions for you: How much are the headlines affecting news-spectators decision making about their own debt, credit, income, savings and spending? And what is your organization’s strategy to adapt as consumer behaviours keep shifting ever more online/mobile which has shifted traditional power away from brands and toward consumers and the platforms they use?