A conversation with Ali Madad, a thought leader on the topic of innovation. Design thinking, by the sounds of it, would be a strictly creative process. Because we have access to so much data, it can be difficult to determine what kind of data do you bring into your design process? Is there a difference in how you use design thinking and data in design versus technology innovation? And how do you find the appropriate place to introduce it, without causing friction in a process that’s already producing results?
[00:00] Welcome to It’s Worth Doing Right. I’m your host, Olivia Hayes; resident creative pragmatist, and the Head of Product Strategy at Accomplice. Design thinking, by the sounds of it, would be a strictly creative process. But we now have a much more mature and nuanced view of the design thinking process: one that has a place for the copious amounts of data we now have access to. But because we have access to so much data, it can be difficult to determine what kind of data you bring into your design process. Is there a difference in how you use design thinking in data and design versus technology innovation? And how do you find the appropriate place to introduce it without causing friction in a process that’s already producing results? To get into specifics, we spoke with someone with a proven track record of using data into innovative projects.
[00:40] Hi, I’m Ali Madad. I’m a principal and co-founder of SCTY, my independent design consultancy.
[00:48] Ali is being humble. He’s an award-winning designer, writer and educator based in NYC. His impact on work for the Coca-Cola Company, Samsung Mobile USA, IBM, Disney, and Pizza Hut makes him the ideal person to help us understand how data is used to innovate.
[01:04] To start with, what do you think the place of design is in overall business strategy?
[01:16] Design has always played a consequential role on business strategy, and in the past decade or so, it’s played an increasingly important and more visible role as seen through companies like McKinsey, Deloitte, and Accenture acquiring design talent as part of their overall business strategy, to companies like Facebook and Google and Amazon increasingly pulling more designer skillsets across their product to improve the overall value proposition to their end consumer. So it’s always played a role, and these days, it’s a much more vital role because of the things that design shapes. They’re rising and changing levels of customer and consumer expectation around that.
[02:03] It used to be that design was only thought of as the finishing touches, the part of the process that made things look good, but the way we think about the role of design is changing – and that includes how we think about the innovation process of technology solutions, and where design fits in.
[02:18] With the rise of things like lean startup, agile development methodology, design thinking – those three have become sometimes used interchangeably, even though they have very different aims. They very often were complimentary. Lean startup focuses more on the market product fit, and evaluating the viability of a business model solution. Agile focuses on the very specific methodology on software development cycles. And design thinking was at the front end of that – in one form, it is the discovery, the problem identification, all the way through solution vetting that would kind of feed through that lifecycle. But they share a lot of common tools, mindsets, and methodologies that make them more than compatible, but complementary. And innovation in that way has always relied on bringing new and useful things to market. So sometimes, one approach is preferable to another.
[03:33] In the past decade or so, I’ve looked at the work from Clay Christiansen out of the Harvard Business School, and his notion of jobs to be done is very complimentary to – and very sympathetic to, and reflective of user-centered design approaches, which privileges the use case or problem as a fulcrum for identifying systemic solutions that cascade up and down.
[04:00] One thing that’s interesting is that when people say the word “design,” I think the thought process is, “oh – aesthetic design!”, but the word design actually encompasses so much more than just aesthetics. Which is what you’re talking about – and getting into those larger implications of actual design.
[04:18] Yeah. I think Steve Jobs gets a lot of credit for putting it out and probably the most ease-oft quoted sort of way, which is “design is not just the way it looks, but it’s how it works.” And so it’s that end-to-end consideration around services, products, experiences, and the relation that has to businesses, and customers, and things like that.
[04:40] Although the term design thinking is used fairly broadly, the actual process of design thinking can vary from product design to technology innovation. And the differences are worth carefully noting.
[04:51] I think there’s a lot of strong parallels. Often, it just comes down to the aims, intents, and the kind of goals. The design thinking process can vary for technology applications as distinct from non-technology applications. A lot of it comes down to a kind of approach and kind of goals. I think in a design approach that’s kind of uncoupled from technology or uncoupled from a product, there is a mentality that it has to be perfect. And in a design thinking approach that is rooted in innovation, and very often in technology, it’s always good enough because the assumptions that we have made and baked into what we’re creating need to be tested and validated. Whether it’s in the market, or in some shape or form. Because that completes the circle, and sometimes you see those two worlds collide when you have a “shipping mentality” that contracts or conflicts with this kind of platonic ideal of what something should be.
[05:58] Constraints often unfairly get a bad rap, but when it comes to design thinking, constraints are often what make your solutions both creative and impactful. Constraints facilitate both alignment and clarity, and the process wouldn’t be effective without them.
[06:12] Constraints are a “hallmark of good design” problem, and especially in an innovation process. The constraints help to set and define boundaries, whether it’s budgetary, time, in some cases, internal stakeholder alignment constraints. Design thinking lets you bring all of the stakeholders to the table, gets you to a point of understanding and alignment around goals and outcomes, and quickly and iteratively demonstrates proof and value for some of the potential emerging technology solutions – as well as hopefully ensure that emerging technology is always tied to some sort of user-centered challenge or problem. And the emerging technology becomes a way to express, or a new way to connect with or identify and cover audiences. So long as you know that thread of what it’s intending to do matches with expectations around what the product service and brand is offering and this emerging technology or innovation solution, that needs to deliver on some of those key criteria.
[07:29] Specific data can be most beneficial at certain points in the innovation process, but what type of data? And where is it most effectively introduced into the process? Those are the nuances in application that can really impact outcomes.
[07:41] Early on in hypothesis-generation mode and discovery, or early solution-finding and problem-vetting, data can help make a case for one of these pathways, or opening up an opportunity. And it could be as simple as “four out of five of our competitors are not doing this x thing – we should start to look at new ways to connect with audiences in x way.” And during the life cycle of product/service/incubation, data may come from different internal stakeholders or early customers, but it’s always intended to really help drive and kind of buttress what’s being worked on. And as it comes into market early or mid-stage, then that’s when data becomes a very critical element to validating assumptions from the earlier stages.
[08:41] Is there any data that you feel like really isn’t that beneficial to the innovation process?
[08:45] I think very often, a lot of clients and sometimes key stakeholders come in with predetermined KPIs and predetermined goals that map and correspond to their own incentive structures, as opposed to having data or those incentives aligned towards the most beneficial outcome for this product or solution.
[09:13] So data is exciting, but it isn’t a silver bullet. Sometimes organizations can fall into a mindset where they think that it might be the magic solution to their challenges… when in reality, it’s a strategic piece of the puzzle, one that is best when integrated with other parts of your business. What are some of the pitfalls that are faced by organizations when thinking of how to incorporate data into their practice of innovation?
[09:34] Well, I think in both cases, whether it’s data or design thinking, a lot of organizations that introduced it, reintroduce it, or elevate it very often do so with this “silver bullet” kind of notion, or magical thinking that it’s going to be the solution for everything. And in both cases, it’s just another tool or methodology or approach that will help you make smarter decisions and help you get to better outcomes. So it has to be an organizational and a culturally disseminated set of practices and approaches for it to really take hold. It can’t be a one-off thing and it can’t be a pet project. It really needs the whole organization to understand that data is a driver for how we make decisions. Design thinking is a methodology for how we determine what we evaluate, and what we bring to market, and who we go after. Bringing those two together, or bringing any one of those – it’s changing every time. Yeah, it’s understanding the process. But it’s also the making sure that those are values and priorities, and not just things that are carted into a meeting, or ushered in as a way to window draft.
[10:56] There are great examples of organizations that are data driven from end-to-end. Netflix had their start when, before they were transitioning to streaming, they would collect all of their ratings in a very explicit way, so they were very explicitly capturing preference. And they moved away from that after having done a million dollar algorithm design contest in the world of streaming, where they don’t need to ask users for any more information, because they know when we’re watching, where we’re watching, how long we’re watching, what we’re watching and what we watch next. All of our implicit behaviors now become their data. And that data then informs all the decisions up and down, from programming to how they curate. With design thinking, you have companies like Apple that go through long incubation periods, or even a company like Pixar, where they approach any given film in a very design thinking friendly way, where they will do the contextual inquiry and ethnographic research to really immerse the teams in the world that they’re trying to understand, empathize with, and create.
[12:14] Because Ali spends every day in the mix, before we ended our conversation. we wanted to get his take on what space within technological innovation he’s currently the most excited about.
[12:23] Personally, I am very key to kind of explore or scratch deeper on the surface of parametric design. So with any sort of data, we are now at a point where big data as the big buzzword has kind of subsided, and has been replaced with and taken all the oxygen out of the room by machine learning, or AI-anything. And the implications that any combination of those have for the design practice is really fascinating. There is an open-source platform called Dropbot, and a module for it called Pagebot created by Dutch topographers that intends to recreate page layout from the ground up in a parametric and programmatic way. So that to me is a very exciting space. There’s a lot of really interesting things happening in variable font technology. I think anything in the hardware space, AI and AR and VR, are fascinating.
[13:30] Every organization is unique, and because of that, their philosophy on how to incorporate data into their process of design thinking or innovating is going to be different. There isn’t one right way to do it, but the most important thing to remember is that data as a tool has to be an organizational mindset. It can’t be thought of as a silver bullet or as a cool marketing phrase. Otherwise, the true opportunity will be missed. A chance to deepen your organization’s ability to identify innovation, and strengthen your design thinking process across outcomes. Companies who master this skill are set to scale.
[14:05] Thanks for joining us on today’s episode. If you’d like to learn more about our family of agencies or give us feedback, visit us at itsworthdoingright.com, or drop us an email at firstname.lastname@example.org. And remember: if it’s worth doing, it’s worth doing right.