Tag Archives: digital

Digital Transformation Dialogues – Part 4 – Creating the Right Culture around Collaboration Tools

[Here’s more from my ongoing dialogue with transformation expert and friend Scott K Wilder. In the last post, we discussed ways to make an older workforce more digitally savvy. Scott ended that post with this: “Personally, I would rather be HipChatted vs. Slacked. But technology sometimes like religion. You have to find out what people are most comfortable with. At Marketo, it was Slack. At Salesforce, it is Chatter. For me, I prefer to be Skyped!. How about you?”]

GA: I’m a reluctant video user. I was always the kid who liked to sit in the very back of the class hunched down behind somebody who played Right Guard on the football team. That being said, I have some issues with chat too. It’s a very interruptive technology. I know that’s it’s super popular with developers – and I see the point particularly in Agile teams. But I always viewed serious code writing as essentially monastic. That may seem ludicrous, but writing large scale software is a real intellectual undertaking – requiring you to hold hundreds of thousands of lines of code in your head and have at least a general sense of how they fit together and what’s there. I’m not convinced you can do that while you’re regularly dropping in and out of chat sessions (or, for that matter, having meetings every 30 minutes). When I was writing large-scale code I pretty much talked to no one. Of course, a vanishingly tiny percentage of people are writing serious code. But I feel the same way about writing – something I do regularly. When I’m writing a piece I care about, I seriously don’t want to be interrupted. So my question really is about protecting culture – you’ve talked about adoption – and creating a culture of usage. I agree that’s important – in fact it’s a far more common failure point. Life being what it is, though, we also have to worry about too much success (and part of adoption is assuring people that culture won’t change too much – even if it will). So how do you create an etiquette culture around collaborative technologies that protects other types of behavior we value? After all, no company wants the family equivalent of everyone whipping out their iPhones at the dinner table…

SW: Ah, now we are getting into a little psychology and ethnography. For me, there are two ways to approach this (business) issue:

  1. Constantly try to understand the different personalities in your company
  2. Consistently establish and communicate company values throughout the organization

In every organization, there are many personality types. Each responds to new challenges in different ways, especially when it comes to adopting new technologies. Individual or team behaviors can be looked at through a Myers Briggs lens. Or you can examine various personas involved.

Ironically, 80% of companies do market segmentation with personas or some other kind approach, but few take the time to do the same thing when trying to figure out how to work with their own employees. Few companies step back and look at the different ways their own people adopt technology. There is often little conversation about how new processes and technologies diffuse throughout an organization. So what’s my point about all of this psycho mumbo jumbo.

Before you can create a culture around the adoption of a new technology, you need to understand the different personality types in your organization. And it helps if you leverage a topography like Myers Briggs, to help understand how people learn or adopt new technologies.

For example some people might prefer to learn on their own either studying a user manual or watching videos before kicking the tires and testing out a new product. Others might prefer to learn with a mentor or teacher to guide them. And others might want to learn by participating with others. The important thing is to first understand how an individual responds and adapt to new ways of doing business.

After you know the different types of people/personalities you are dealing with, you can begin to focus a culture that fosters the adoption of new technologies while protecting people’s values (or how they want to start using the new technology).

Finally, the challenge is getting these different types of people to function on a day-to-day basis with each other. This will be easier if you have provide a comfortable and safe environment for them to learn at their own speed and in their own way.

Secondly, when creating an etiquette culture around collaborative technologies, it’s important to present them to your employees by showing how they map to your core company values (This assumes you have company values). Atlassian, my current employer, has very strong values which are reviewed every time the company works on a project. Some of them include:

  • Don’t #@!% the customer: This statement promotes honesty and transparency. The company knows that their Customers are their lifeblood. Without happy customers, they are doomed
  • Play, as a team: As they say “We spend a huge amount of our time at work. So the more that time doesn’t feel like “work,” the better. We can be serious, without taking ourselves too seriously. We strive to put what’s right for the team first – whether in a meeting room or on a football pitch.”

These are just two of the values. There are others, but each one is used to help keep every employee aligned and heading towards the company’s True North, especially when adopting a new collaborative technology or trying to change behavior across the organization.

Finally, collaboration has no beginning nor end It is a continuous journey that involves multiple parts of your organization.

GA: There’s a lot here to respond to. I’m totally on board with your thoughts around corporate culture and values. Most companies pretend to have values – some actually do. And while I’ve argued in some other cases that you can drive analytics without necessarily having top-down support (though it sure does help), culture building is either hierarchic or anarchic – and anarchic rarely works as a model. That isn’t to say that individual managers can’t create micro-cultures inside a larger organization. They do – and pretty constantly. But those micro-cultures – for good or ill – are always getting worn down and eroded by the broader culture. There’s no place where the impact of senior folks is more pronounced than on setting the tone for this kind of culture building – and, as I’ve argued elsewhere, culture building isn’t done with words. In the beginning was the deed! You can talk “Don’t #@!% the customertill you’re blue in the face, but the first time an executive makes a decision to the contrary, all that talk will be less than worthless (and I do mean less since it creates negative value in the company). That’s one good reason why it’s important to have values you A) actually care about and B) can reasonably live up to.

I’m less comfortable with tests like Myers-Briggs for employee segmentation. I’ve never been confident that personality tests capture anything real. I know they have a lot of fans (and a lot of fans among people whose opinions I respect) – but I’m unconvinced. Sure, we all see ourselves in the results of these tests. But we see ourselves in our horoscopes too. Self identification isn’t objective verification. But I’ll give you the validity of personality types and still question whether it’s a good tool to help drive cultural adoption (and proper etiquette) around social technologies. I’ll buy that segmentation would bring something to crafting a change management and adoption strategy – but would I use personality types or would I use things like rank, role, and behavior?

Convince me if you can!

Finally, let’s talk technology. I’d love to get your thoughts on what types of collaborative technologies make the biggest difference in an organization. And I’d also like your thoughts on whether that’s even the right question. Do you need to think about a collaborative suite? Will one tool likely die on the vine where a constellation of tools might work? I’ve seen both approaches fail – but that’s never conclusive. We live in a “baseball” world where failure is always the most common outcome.

 

Digital Transformation Dialogues – Part 3 – Bringing an Older Workforce up to Speed and Driving Adoption of Digital Tools

[Here’s more from my ongoing dialogue with transformation expert and friend Scott K Wilder. In the last post, we discussed the role of Millennials in balancing an older workforce. But I wanted a little more detail on how to get an older workforce more digitally aware…]

SW: I probably forgot this one because I am an older guy, but I’m also someone who thinks it’s every marketer’s responsibility to learn digital technology. Before I directly answer the question, let me give you an example. My son is really into drones and wants me to take him to some national parks so he can fly his drone. Before I make a road trip with him, however, I want to master drones, so I hired a drone coach. After all, I am the one who is ultimately responsible for my son’s safety. Working at as a Digital Marketer or Digital Employee requires the same commitment. The only difference, however, is that companies need to play a bit of the parental role and provide a clear path for their employees to learn about technology.

This can be done by paying for courses (Marketo, my former employer, pays for its employees to take courses at Lynda.com). It can be done by making ‘learning certain technologies’ as required for the job. Instead of saying you learn it or you lose it (your job), position this change as an opportunity to skill up — and that the company is investing in the future (in its best asset, its employees).

Companies also should provide career guidance — either for older employees to find other opportunities within their company or with a company’s partner. Training, career guidance are not only great retention tools, but also build loyalty after an employee moves on.

Companies also need to gently require that digital technologies be used in their everyday business practices. If the older person wants to remain part of the company, they will have to hop on the digital bus. And like the Magic School Bus (a book my kid loves), it will be a journey into unknown — with lots of opportunity to learn, a bit of uncertainty and a fun adventure. You know what. Even outside the office, they will feel as if they are on the Magic School Bus because by learning technology, older folks can have a more enriched life. My son Facetimes and Skypes with his Grandma twice a week.

Why should companies do this? Why should they make this investment? Several reasons, such as older workers tend to be loyal, older workers already know ‘your business’. Companies should also build incentive systems — gamify their career development — so they will be motivated to take on the exciting challenge of improving their skills.

Final note: Being Digital is more than just using the internet and Facebook. Companies should also figure out what digital technologies will help these older workers do their job better. If they need to be on social media, teach them Hootsuite. If they need to manage email programs, teach them Autopilot or Exact Target. If they need to collaborate better, be their guide while they learn Slack or HipChat.

GA: There’s a couple of points that I want to particularly call-out there. One is that company’s aren’t taking full advantage of the explosion in high-quality educational courseware that’s available these days. Sure, lots of folks will do this on their own, but not everyone is sufficiently motivated. I’ve always said my number one guiding principal – and the reason transformation is so hard – is that EVERYONE IS FUNDAMENTALLY LAZY. Giving people real incentives and formal guidance on courseware so that it’s part of an employee’s basic career development is really easy to do and I think pays tremendous dividends. If your company hasn’t curated public courseware for specific career-tracks and incentivized your employees to take advantage, you should be kicking your HR team’s butt (just my humble opinion).

I’m also a huge fan of the idea (as you know) that people have to DO stuff. And I’m glad you brought up the technologies because that’s the next (and last) area I wanted to explore. A lot of the digital technologies are fundamentally collaborative. But that can make adoption critical to their success. I know you’ve been living this problem – how do you get a team (and keep my older, non-digital workers in mind) to adopt tools like Slack?

SW: Gary, why are you always asking me the hard questions? I think you ‘re correct in focusing on ‘the team’ vs. ‘the company’ and trying to mandate day 1 that a whole company start using something like Slack.

They key is to start with one group.  Pick a team that seems receptive to taking on new ways of doing things — especially when it comes to digital technology. And within that group, you should also identify a few key digital change agents, early adopters, who are willing to not only try out the new technology, but also be champions for it.

Create a program for these digital champions. It can be rewards focused, but even better,  show them how sharing their knowledge and experience will help them learn a new technology even better and make them more marketable. Intuit, where I spent almost a full decade, has a philosophy called “Learn Teach Learn.” The only way to really learn something is to teach it to others (Intuit has a great learning culture!).

Of course, there is another option. You could see if any group in the company is currently using Slack and make them that group ‘your change agents. At Marketo, it was actually the company’s commuters — employees who took a small shuttle bus that looked like one of those vans old age homes use to transport its frail residents – who started using Slack. They let their fellow workers know if they wanted the bus to wait for them or if they wanted the van to turn around and pick up someone they forgot. My group of commuters called our Slack group, The Purple Lobster.

The Slack group was called the Purple Lobster because that’s what we called the van. We picked purple because that was Marketo’s company color. And lobster because it wasn’t the fastest moving vehicle on Highway 101.

And like a lobster slithering in the sand (sorry about pushing the poetic envelop here) slowly, but surely ,other commuting groups started to using Slack. Eventually, product teams started using it And finally, the CTO and his team made the call to not fight the crowd and force the company to use another tool, like Chatter. Instead, CIO convinced his fellow executives to adopt Slack across the company. It was a brilliant ‘if you can’t beat them, then join them’ strategy.

If you identify a group using Slack, challenge them to go completely cold Turkey. See if they are willing to only use Slack only (no email) for a week or so. At Atlassian, I had my hand Slacked when I tried to send an email to someone with a simple question. They recommended I use their Slack like product, Hipchat. And now, I only have 20 emails in my inbox. How many of you have only 20 emails in your corporate email inbox?

If you are not so lucky to find early adopters, you need to find a group of people who are most like to use the new technology. If there are some older folks on the team, pair them up with the younger wipper snappers. Or provide some training.

The key in all this is not to focus on technology. Instead, treat the change to Slack or any other digital technology as a change management exercise. Focus on adoption — education, onboarding and engagement. None of this should be done in a vacuum. You need someone to shepherd the process. Someone who can be a guide, a teacher, a problem solver and yes, a true change agent.

Other considerations include rewarding people for their efforts and successes. Gamify the process! In doing so, make sure to acknowledge people’s efforts for trying. Don’t make the same mistake most schools make and only pass people for knowing the answer. As Carol Dweck, well known motivational researcher,  points out, children praised for hard work chose problems that promised increased learning (vs. just getting the right answer). This also applies to adults. Really!

The key here is to alter someone’s mindset. Instead of rewarding (just giving them a bonus) or punishing someone (not promoting them) for adopting a new technology, recognize their effort and hard work. The end result will be they might adopt taking on new challenges and succeeding at them. Even if it means learning and using something like Slack.

Finally good old training is important. It always amazes me how many companies introduce a new technology and offer one time training. Usually during a three hour class. If you are licensing a technology like Slack, see if they can conduct monthly webinars to answer questions (if not, you offer it). Also have videos and Q&As available for your staff.

Personally, I would rather be HipChatted vs. Slacked. But technology sometimes like religion. You have to find out what people are most comfortable with. At Marketo, it was Slack. At Salesforce, it is Chatter. For me, I prefer to be Skyped!. How about you?

Digital Transformation Dialogs

I’m going to wrap up this extended series on digital transformation with a back-and-forth dialog with an old friend of mine. I’ve known Scott K. Wilder since the early days of Web Analytics. He’s been an industry leader helping companies build communities, adapt to an increasingly social world, and drive digital transformation. In some of this current work, Scott has been working with companies to adopt collaborative working suites for their customers, partners and employees – which I think is a huge part of internal digital transformation. So I thought a conversation on the pitfalls and challenges might be interesting and useful.

GA: We all see these hype-cycle trends and right now there’s a lot of interest in digital transformation at the enterprise level. I think that’s driven by the fact that most large enterprises have tried pretty seriously for a while now to get better at digital and are frustrated with the results. Do you agree?

SW: Good question.

When you read white papers about the latest trends in the enterprise space, most of them highlight the importance of each company being digital transformed. This usually means leaving a legacy approach or operation and instead leveraging a new approach or business model that embraces technology.

Unfortunately, most companies fail when they undertake this endeavor. Sometimes they fail because just pay lip service to this initiative, never do anything beyond placing the goal of ‘going digital’ on a powerpoint slide they give a company All-Hands (I have witnessed this first hand). And sometimes, they just test out bunch of different programs without thinking through desired outcomes. (They throw a lot of virtual stuff against the internet wall hoping that something sticks).

Undergoing a Digital Transformation means many things to many people. It can imply focusing more on the customer. Or it can mean enabling employees collaborate better together. At the end of the day, however, a company needs to first focus on one simple end state. One change in behavior! Rather than trying to boil the whole ocean at once and try to do implement massive digital transformation across an organization, it’s better to start with a  simple project, try to leverage technology to accomplish a desired outcome, learn from the experience and then share the success with other parts of the organization

Start first with a relatively simple goal. And if you really want to change an organization, see if you can get employees volunteer to be your soldiers in arms and then closely work with them to define what digital success looks like. It could be as something getting employees to digitalize their interaction with each other more  or leveraging technology to improve a VOC process. Whatever it is. Start with one project.

Here’s one approach. Once the goal is to define, then ask for volunteers to work on figuring out how to achieve the desired outcome. No digital program or initiative is going to be successful without employee buy – in and involvement, so it behooves CEOs to find a bunch of enthusiastic volunteers to figure out the ‘how’ (If you remember you calculus Y = (x)x Senior managers can decide on the Y, and then let their team figure out the X or inputs.

Digital Transformations often fail because:

  • Executives often decide their company goals and then impose their approach on the employees. Digital Transformation initiatives also fail because CEOs want to change whole culture overnight. Unfortunately, however, they often forget Rome was not built in day. Even though a true Digital Transformation is often a journey, it is also important to start simple. Very simple!
  • There’s no buy in at the mid-level ranks in the company
  • There’s no True North or desired goal
  • There’s too much attention on the technology and not the cultural impact.

I have read articles that tell you true cultural change can only happen if you eliminate political infighting, distribute your decision making, etc. While all of that is important, it will require gutting your organization, laying off a lot of people and hand-picking new hires if you want to change things quickly.

To truly change a culture, however start simple. Pick a goal. Ask for employees to volunteer to work on it (take other work off their plate so they don’t have to work after house). Ask them to to involve leveraging digital technologies. Give the team room to succeed or fail.  Most importantly, be their guide along the way.

Once this small team completes their project, celebrate their success in front of others in the company. Have them highlight how they leveraged technology.

Once this group is successful, anoint each team member to be a digital transformation ambassador and have them then move into other groups of the organization and share their learnings, experiences, etc.

GA: I’m a big believer in the idea that to change culture you have to change behavior – that means doing things not talking about them. I like the idea of a targeted approach – huge organizational changes are obviously incredibly risky. That being said, I feel like most of what you’ve talked about could be applied to any kind of transformation project – digital or otherwise. I’m not disagreeing with that, but I’m curious if you agree that digital presents some unique challenges to the large enterprise. And if you do agree, what are those challenges and do they change/drive any aspects of a transformation strategy?

SW: There are definitely challenges in driving any type of transformative change in an enterprise environment. Here’s a list of challenges preventing a smooth adoption of digital technologies or hindering the ability to digitally transform an organization

As they say. It’s hard to teach an old dog new tricks. Companies get stuck in their old ways of doing things. For example, even though companies are testing the waters with Slack and Hipchat, two great collaborative platforms, few have made any progress in being weaned (a bit) off of email. For example, we all complain about email but refuse to reduce how often we use it). Part of the problem is the result is that those individuals, who are tasked with driving change in the organization actually tend to be the biggest resisters to change. The IT department, who I will pick on here, usually are decision makers and keepers of the digital platform budgets do not want to try something new. (Marketing is slowly getting more say here, but most marketing leads don’t understand new technologies). So IT and even Marketing wait as long as possible to make a decision about adopting newer collaborative technologies, such as Slack or Hipchat. And while they are doing an elaborate evaluation process, today’s tech savvy staff often just jumps in and starts using the latest and greatest technologies. They don’t ask for permission first. This was the case at Marketo with Slack. First, a small group of employees starting using it and soon others jumped in. There was resistance at the highest parts of the company. Eventually, IT, however had no choice and how to follow the wisdom of the crowd. Survey Monkey also started out this way. There are other challenges as well. Solution: Companies need do a better job at knowing understanding what tools their teams want to use and why they want to use them. If the troops are using Google Docs, for example, management needs to embrace this and not try and force their way (in this case, the Microsoft Office 365 way) down the throats of their employees. If there are security concerns, figure out a solution.

GA: I’ll just note that in many ways this reflects my discussion of a Reverse Hierarchy of Understanding in organizations

…What else?

SW:   Data and Privacy Issues: Companies, rightly so, are always concerned about data leakage, data security and privacy issues. Enterprises, especially the public ones and the ones in important transaction industries like Finance or Health Care, have to be sensitive to how data is shared within an organization. Solution: If an organization wants to adopt a newer technology, management needs to do more research in how other companies adopt newer technology while protecting their company secrets. Few companies develop breakthrough technologies and systems that they are the first to try something new. Probably someone has already created a similar service or implemented a similar technology. They have probably already dealt with similar issues. I am not saying just copy what they did but rather learn from their mistakes. Or what they did well.

An older workforce: A third challenge is that many enterprises attract an older workforce and/or are not sure how to integrate millennials into their organization. As I pointed out in my book, Millennial Leaders, it’s important to embrace a younger workforce and place these individuals on teams where they can help advise key decision makers. Younger employees are more likely to adopt new approaches, new technologies and new ways of doing things. Solution: Bring millennials into digital related conversations sooner than later. While decision making can still be top down, it’s important to give these younger folks a voice.

GA: Okay – I know you have more thoughts on this but I’m going to stop right there because I know you’re an expert on this Millennial stuff and I want to delve into it a bit. But that’s probably a discussion for Post #2…

How to Drive Digital Transformation when You’re Not a Digital Expert : Addressing the Reverse Hierarchy of Understanding

In my last post I described some of the biggest challenges to a traditional enterprise trying to drive digital transformation. This isn’t just the usual “this stuff is hard” blather – there are real hurdles for the traditional large enterprise trying to do digital well. The pace of change and frictionless competition drive organizations used to winning through “weight of metal” not agility, crazy. The need for customer-centricity penalizes organizations setup in careful siloes. And these very real hurdles are exacerbated by the way digital often creates poor decision-making in otherwise skilled organizations because of what I termed the reverse hierarchy of understanding.

The reverse hierarchy of understanding is a pretty simple concept. Organizations work best when the most senior folks know the most about the business. When, in other words, knowledge and seniority track. For the most part (and despite a penchant for folks lower down in the organization to always think otherwise), I think they do track rather well in most companies. That, at least, has been my fairly consistent experience.

There are, of course, many pockets of specialized knowledge in a large company where knowledge and seniority don’t track. The CFO may not be able to drive TM1. The CTO probably doesn’t know Swift. That’s not a problem. However, when something is both strategic and core to the business, it’s critical that knowledge and seniority track appropriately. If they don’t, then it’s hard for the enterprise to make good decisions. The people who are usually empowered to make decisions aren’t as qualified as they typically are, and the folks who have the specific knowledge probably don’t have either the strategic skills or business understanding to fill-in. And, of course, they probably don’t have the power either.

Digital can create exactly this inversion in the appropriate hierarchy of decision-making in the traditional enterprise, and it does so at many levels in the organization. Digital has become strategic and core far more rapidly than most large organizations can adapt, creating reverse hierarchies of understanding that can cripple efforts to do digital better.

So if you want to transform a traditional business and you know your organization has a reverse hierarchy of understanding (or maybe just a complete lack of understanding at every level), what do you do?

There’s not one answer of course. No magic key to unlocking the secret to digital transformation. And I’ve written plenty of stuff previously on ways to do digital better – all of which still applies. But here are some strategies that I think might help – strategies geared toward tackling the specific problem created by reverse hierarchies of understanding.

 

Incubation

I’m sensitive to the many draw-backs to incubating digital inside a larger organization. If incubation succeeds, then it creates long-term integration challenges. It potentially retards the growth of digital expertise in the main business and it may even cannibalize what digital knowledge there is in the organization. These are all real negatives. Despite that, I’ve seen incubation work fairly effectively as a strategy. Incubation creates a protected pocket in the organization that can be staffed and setup in a way that creates the desired knowledge hierarchy through most levels.  Would I always recommend incubation? Absolutely not. In many organizations, years of at least partial learning and transfusions of outside talent have created enough digital savvy so that incubation is unnecessary and probably undesirable. If digital knowledge in your organization is still nascent and particularly if you have layers of management still skeptical or negative to digital, then incubation is a strategy to consider.

 

Transfusion

And speaking of talent transfusions, the role of appropriate hiring in effectively transforming the organization can hardly be overstated. The best, simplest and most impactful way to address the reverse hierarchy of understanding is to…fix the problem. And the easiest way to fix the problem is by hiring folks with deep digital understanding at multiple levels of the organization. In some cases, of course, this means hiring someone to run digital. If you’re a traditional enterprise looking to hire a chief digital officer, the natural place to look is to organization’s that are great in digital – especially the companies that dominate the Web and that we all, rightly, admire. I tell my clients that’s a mistake. It’s not that those folks aren’t really good at digital; they are. What they aren’t good at is digital transformation. If you’ve grown up managing digital platforms and marketing for a digital pure-play, chances are you’re going to be massively frustrated trying to change a traditional enterprise. To drive transformation, you have to be a great coach. That isn’t at all the same as being a great player. In fact, not only isn’t it the same, it’s negatively correlated. The best coaches are almost NEVER the best players.

Getting the right person to lead digital isn’t the place where most organizations go wrong though. If you’re committed to digital transformation, you need to look for digital savvy in every hiring decision that is at all related to your digital enterprise. You need digital savvy in HR, in accounting, analytics, in customer, in supply chain, in branding and corporate communication. Etc. Etc. This is the long game, but it’s ultimately the most important game you’ll play in digital transformation – especially when you’re trying to drive transformation outside of massive disruption. In my last post, I mentioned FDR’s many efforts to prepare the U.S. for WWII before there was any political consensus for war. Every leader is constrained by the realities on the ground. Great leaders find ways to at least lay the essential groundwork for transformation BEFORE – not after – disaster strikes. You need to make sure that digital savvy becomes a basic qualifier for a wide range of positions in your organization.

 

Analytics

Dare I say that analytics has the potential to play a decisive role in solving the reverse hierarchy of understanding? Well, at the very least, it can be a powerful tool. In a normal hierarchy of understanding, seniority comes pre-loaded with better intuitions. Intuitions born of both experience and selection. And those intuitions, naturally, drive to better decisions. It’s darn hard to replace those intuitions, but analytics is a great leveler. A good analyst may not be quite the decision-maker that an experienced expert is – but at the very least a good analyst equipped with relevant data will come much closer to that level of competent decisioning than would otherwise be possible.

Thankfully, this works both ways. Where senior decision-makers can’t rely on their experience and knowledge, they, too, benefit from analytics to close the gap. An executive willing to look at analytics and learn may not be quite in the league of an experienced digital expert, but they can come surprisingly close.

This works all up and down the organization.

So how do you get your team using analytics? I addressed this in depth in a series of posts on building analytic culture. Read this and this. It’s good stuff. But here’s a simple management technique that can help drive your whole team to start using analytics. Every time there’s an argument over something, instead of voicing an opinion, ask for the numbers. If your team is debating whether to deliver Feature X or Feature Y in digital, ask questions like “What do our customers say is more important?” or “Which do high-value customers say they’ll use more?”

Ask questions about what gets used more. About whether people like an experience. About whether people who do something are actually more likely to convert. If you keep asking questions, eventually people are going to start getting used to thinking this way and will start asking (and answering) the questions themselves.

Way back in the early days of Semphonic, I often had junior programmers ask me how to do some coding task. At the time, I was still a pretty solid programmer with years of experience writing commercial software in C++. But since I wasn’t actively programming and my memory tends to be a bit short-term, I almost never just knew the answer. Instead, I’d ask Google. Almost always, I could find some code that solved the problem with only a few minutes’ search. Usually, we’d do this together staring at my screen. Eventually, they got the message and bypassed me by looking for code directly on Google.

That’s a win.

Nowadays, programmers do this automatically. But back in the aughts, I had to teach programmers that the easiest way to solve most coding problems is to find examples on Google. In ten years, looking at digital analytics and voice of customer will be second-nature throughout your organization.  But for right now, if you can make your team do the analytics work to answer the types of questions I’ve outlined above, you’ll have dramatically raised the level of digital sophistication in your organization. This isn’t as foreign to most good enterprise leaders as I used to think. Sure, folks at the top of most companies are used to offering their opinions. But they’re also pretty experienced at having to make decisions in areas where they aren’t that expert and they know that asking questions is a powerful tool for pushing people to demonstrate (or arrive at) understanding. The key is knowing the right questions to ask. In digital, that usually means asking customer-focused questions like the one’s I enumerated above.

 

Consulting

I’m probably too deeply involved in the sausage-making to give good advice on how organizations should use consulting to drive transformation. But here’s a few pointers that I think are worth bearing in mind. Consulting is a tempting way to solve a reverse hierarchy of understanding. You can bring in hired guns to build a digital strategy or drive specific digital initiatives. And if you’re lucky or choose wisely, there’s no reason why consultants can’t provide real benefits – helping speed up digital initiatives and supplement your organizational expertise. I genuinely believe we do this on a pretty consistent basis. Nevertheless, consultants don’t fix the problems created by a reverse hierarchy of understanding; they are, at best, a band aid. Not only is it too expensive to pay consultants to make your decisions on a continuing basis, it just doesn’t work very well. There are so many reasons why it doesn’t work well that I can attempt only a very partial enumeration: outside of a specific project, your consultant’s KPIs are almost never well aligned with your KPIs (we’re measured by how much stuff we sell), it’s difficult to integrate consultants into a chain of command and often damaging if you try too hard to do so, consultants can become a crutch for weaker managers, and consultants rarely understand your business well enough to make detailed tactical decisions.

Don’t get me wrong. Building talent internally takes time and there aren’t many traditional enterprises where I wouldn’t honestly recommend the thoughtful use of consulting services to help drive digital transformation. Just don’t lose sight of the fact that most of the work is always going to be yours.

 

That last sentence probably rings true across every kind of problem! And while digital transformation is legitimately hard and some of the challenges digital presents ARE different, it’s good to keep in mind that in many respects it is just another problem.

I’ve never believed in one “right” organization, and when it comes to digital transformation there are strong arguments both for and against incubation. I think a decision around incubation ultimately comes down to whether digital needs protection or just expertise. If the former, incubation is probably necessary. If the latter, it may not be. Similarly, we’re all used to the idea that if we need new expertise in an organization we probably have to hire it. But digital introduces two twists. First, the best candidate to lead a digital transformation isn’t necessarily the best digital candidate. Second, real digital transformation doesn’t just come from having a leader or a digital organization. You should bake digital qualifications into hiring at almost every level of your organization. It’s the long game, but it will make a huge difference. And when it comes to leveling the playing field when faced with a reverse hierarchy of knowledge, remember that analytics is your friend. Teaching the organization to use analytics doesn’t require you to be an analytics wizard. It mostly demands that you ask the right questions. Over and over. Finally, and this really is no different in digital transformation than anywhere else, consulting is kind of like a cold medicine – it fixes symptoms but it doesn’t cure the disease. That doesn’t mean I don’t want my bottle of Nyquil handy when I have a cold! It just means I know I won’t wake up all better. The mere fact of a reverse hierarchy of understanding can make over-reliance on consulting a temptation. When you’re used to knowing better than everyone, it’s kind of scary when you don’t. Make sure your digital strategy includes thought about the way to use and not abuse your consulting partners (and no, don’t expect that to come from even the best consultants).

Keep these four lessons in mind, and you’re at least half-way to a real strategy for transformation.

Frictionless Competition and the Surprising Monopolization of the Internet

In the last few months I’ve been spending quite a bit of time thinking about the challenges in physical retail – stores. I’m going to be talking much more about that in the months to come, but thinking about the challenges in physical retail and whether and to what extent digital techniques might help, I’ve also had to think about why digital retail has evolved the way it has.

There’s no doubt that digital has disrupted and hurt traditional retail. But it’s a mistake to attribute that solely to advantages inherent in digital. After all, if it was just a matter of digital being superior to B&M, then Borders should have been fine moving online. That didn’t work out so well.

In fact, one of the most interesting aspects of our digital world is how a perfect leveling of the playing field has produced such a strong tendency to natural monopoly. This isn’t just about retail. In most of the key areas of internet – from retail to video streaming to music to search to ride summoning, we’ve seen an extraordinary tendency toward massive consolidation around a single leader.

It’s not exactly what most of us expected. By eliminating most barriers to entry, creating frictionless geographies, and creating technology environments that scale seamlessly to almost any size, the digital world has removed many of the traditional bastions of monopoly. Old-world monopolies used to spring from cases where scale precluded competition. If, for example, you owned the pipes that carried gas to homes or the wires that carried electricity, it was incredibly hard for anyone else to compete.

In today’s world, that kind of ownership has mostly vanished. You could argue that if you own search you own the pipes to the Web. But the analogy doesn’t hold. It doesn’t hold because anybody can create a competing search system at any time and every single internet user can have instant access to it. It doesn’t hold because there are multiple ways to pipe through the internet besides search. And it doesn’t hold because there really are no physical barriers to building or deploying that alternative search system.

So it wouldn’t be unreasonable to expect the digital world to have morphed into a wild west of tiny artisanal companies with meteoric rises, equally sudden collapses, and constant, ubiquitous competition. Mostly, though, that’s not the way it looks at all. It looks as if monopoly, despite the absence of physical barriers, is actually a more powerful tendency in the digital world than the physical world.

It’s not that hard to understand why things have gone this way. Natural monopolies around things like electricity delivery occurred because of the immense friction involved in setting up the delivery system. Economies of scale were absolutely decisive in such situations. But most traditional markets are resilient to natural monopoly because of fundamental facts of the physical world that worked AGAINST too much scale. In the physical world, it makes perfect sense to have gas stations on the opposite side of a street. And it’s quite likely that two such stations can not only co-exist but thrive despite their close proximity. After all, it’s a pain to cross the street when you want to get gas. I may prefer Whole Foods to Safeway or vice versa. But I often go the grocery store that’s closest to me regardless of brand. And when I lived in San Francisco I bought most of my Diet Coke and impulse snacks at the corner store up my block. No, it wasn’t nice and it wasn’t cheap. But it sure was close. I may like Sol Food in San Rafael better than Los Moles, but so do a lot of other people – and I hate standing in line.

The natural friction that the physical world carries in terms of geographic convenience and capacity help ensure that countless niches for delivery exist. Like my old corner store, in the physical world, you can o be worse at everything except location and still thrive.

That doesn’t happen in the digital world.

It turns out – and I guess this should be no surprise – that in a frictionless world, any small advantage can be decisive. A grocery has to be a LOT better than its competitors to get me to drive an extra 10 minutes. But online, the best grocery is always just a few milliseconds away.

It doesn’t have to be a lot better. In fact, the difference can be incredibly tiny. Absent friction, the size of the advantage is no longer that meaningful. The digital world can make even tiny advantages decisive.

So why doesn’t every aspect of the digital world turn into a monopoly?

The answer lies in segmentation. A very small advantage may be decisive in the digital world. But it’s hard to have an advantage to EVERYONE.

In areas like news and entertainment, for example, it’s impossible to produce content that is better for everyone. Age, education, interest, background, geography and countless other factors create an infinity of micro-fractures. Not only is the content itself differentiated, but it’s creation is almost equally fractured. A.O. Scott could no more produce a version of Real Housewives than Andy Cohen could write a NY Times film review.

Content creation turns out to be friction-full in a way that was somewhat obscured by the old limitations in distribution. In fact, it appears that the market for segmented content and the ability of content to create barriers to consolidation is almost limitless. That’s why there’s almost nothing so important to becoming a good digital company than content creation. It’s the best way there is to guard your marketspace.

All this suggests that there are two paths to success in the digital world. One path involves scale and the other segmentation. They aren’t mutually exclusive and the companies that do both well are formidable indeed.

 

It’s only a little more than a month till the Digital Analytics Hub in Monterey and a chance to talk all things digital – both practical and philosophical. After all, there is no monopoly on great conversation. Looking forward to talking deep analytics, natural monopolies, digital transformation and digital advantage!

Organizing the Digital Enterprise

At the Digital Analytics Hub in Europe I facilitated a conversation around enterprise digital transformation. We covered a lot of interesting ground, but organizing digital in the enterprise was the most challenging part of that discussion.

It’s a topic you can easily find yourself going around in circles with as people trot out opinions that sound right but sail past each other. That’s especially true since different organizations start (and want to finish) in very different places.

To get around that, I framed the problem in “state-of-nature” terms. If you were starting a digital organization from scratch in an enterprise, how would you organize and staff it?

But before we could answer that question, we had to consider something even more basic.

Should a “digital” organization be separate?

There’s a pretty strong sense these days that walling off digital from the rest of the organization gets things wrong from the outset. Digital should be embedded right into the DNA of the core organization. In a mature organization, there was a pretty broad consensus that digital isn’t a separate function. On the other hand, what if you’re not mature? Can you embed digital directly and grow it right if it’s inside the huge, complex structures that pervade an existing large enterprise? Even strong proponents of the “digital needs to be organic in the organization” point of view seemed to concede that incubation as a separate organization is often necessary to getting digital done and setup right. Of course, taking the incubation strategy is going to leave you with an organizational debt that at some point will have to be paid. The more successful you are and the larger and faster digital grows, the harder it’s going to be to re-integrate digital back into the organization.

I see both sides of this argument (and I’m sure there are more than two sides to be had). I’m just not a big believer in hard-and-fast right answers when it comes to organizational design.

If you have a strong digitally-experienced leader on your executive team and you have solid relationships between marketing and IT, maybe you try to transform digitally within your existing structures. If you’re not that lucky (and that is pretty lucky), maybe incubation with a strategy for integration is the right answer.

Having gotten to the point where most people conceded that incubation might sometimes be necessary, we returned to the “state-of-nature” question and discussed building out an incubated organization. Most people set product teams at the heart of that organization and agreed that these product teams should be organized very much along the lines that I described in my videos on enterprise transformation: agile-based product teams that include IT, creative and analytics people (behavioral, customer and attitudinal) all working together. In this model, there’s no pass-off from design to implementation to measurement to testing. The same teams that built a project optimize it – and there’s analytics at every step of the process.

I believe this is an incredibly powerful model for getting digital products right – and it’s a model that resonated across a pretty wide swath of different organizations – from giant retailers to very modest start-ups.

But it’s far from a complete answer to creating a digital organization.

Suppose you have these great integrated teams for each digital product, how do you handle all the ancillary functions that the large enterprise has developed? Things like finance and HR, for example. Do they need to be re-created inside a digital organization?

My reaction – and it was common – was that such functions probably don’t need to be re-created inside digital. Including these functions in digital doesn’t seem fundamental to getting digital right.

This point-of-view, however, was immediately challenged when it came to HR. The difficulties of digital hiring are well known – and it isn’t just finding resources. Traditional HR approaches to finding people, vetting candidates, compensation, and promotion bands are all problematic in digital. And if you get the people element wrong, everything else is doomed.

So once again, if you’ve got HR folks willing to work with and adapt to the needs of your digital leader, maybe you can leave existing structures intact and keep HR centralized. But HR is the wrong place to wimp out and leave your digital team without the power to execute the way they need to.

Bottom line? If my digital leader really wanted to own their own HR, I’d say yes.

Other functions? I don’t really know. Is it fundamental to digital execution? Does it need to be done differently in digital? Wherever the answer is yes, then it’s going to be a debate about whether it should live inside an incubated digital organization or be an outside service to it.

There’s another challenge that cuts even closer to the bone and lies at the heart of the challenge to the large enterprise. If you have a single digital product (like a pure-play startup might), you don’t have to worry about the relationship between and across teams and functions. But in a larger enterprise – even when it’s incubated – digital is going to require multiple product teams.

How do management lines work across those teams? Are the IT folks across product teams in the Digital IT organization and are they “managed” by Digital IT? Or are they managed by their Product Owner? In one sense, the answer seems obvious. On a day-to-day basis they are managed by their Product Owner. But who owns their career? What’s a career path like? How do Digital IT folks (or analysts) across product teams communicate? Who makes centralized decisions about key technology infrastructure? Who owns the customer?

Every one of these is a deep, important question with real ramifications for how the organization works and how you take a single product model and scale it into something that preserves the magic of the integrated team but adapts to the reality of the large, multi-function enterprise.

It was here, not surprisingly, that one of the participants in our DA Hub conversation trotted out the “dotted line”. Now it happened to be a consultant from a fellow big-4 and I (too glibly, I’m afraid) responded that “dotted lines are what consultants draw when they don’t have a good answer to a problem”.

I both regret and endorse this answer. I regret it because it was far too glib a response to what is, in one sense, probably the right answer. I endorse it because I think it’s true. God knows I’ve drawn these dotted lines before. When we draw a dotted line we essentially leave it up to the organization to organically figure out how it should work in day-to-day practice. That’s not necessarily a bad thing. It’s probably the right answer in a lot of cases. But we shouldn’t kid ourselves that just because it might be the right answer that makes it a good answer. It’s not. It’s a “we’re not the right people at the right time to answer this question” kind of answer. Knowing enough to know you’re not the right people at the right time is a good thing, but it would be a mistake to confuse that with actually having a good answer to the question.

So here’s my best attempt at a non-dotted line organization that integrates Product Teams into a broader structure. It seems clear to me that you need some centralized capabilities within each function. For Digital IT, as an example, these centralized teams provide shared services including enterprise technology selection, key standards and data governance. In analytics, the centralized team will be responsible for the overall customer journey mapping, analytics technology selection and standardization, a centralized analytics warehouse, and standards around implementation and reporting.

How big and inclusive does the centralized team need to be? Thinking there’s one right answer to this question is a kind of disease akin to thinking there’s some right answer to questions like “how large should government be?” There isn’t. I tend to be in the “as small as practical” school when it comes to centralization – both politically and in the enterprise. The best IT, the best creative, the best analytics is done when it’s closest to the business – that means out there in those Product teams. That also means making sure you don’t incent your best people out of the product teams into centralized roles so that they can “advance” and make more money.

It used to drive me crazy to see good teachers promoted to administrative roles in schools. You can’t blame the teachers. When you’ve got a family to feed, a house to buy, a nice to car to own, you’re not going to stay a teacher when your only path to more money and prestige is becoming an assistant principal. But you don’t see the Cleveland Cavaliers promoting Lebron from player to coach. It’s a terrible mistake to confuse rank with value.

I’m a big believer in WIDE salary bands. One great developer is worth an army of offshore programmers and is likely worth more than the person managing them. Don’t force your best people to Peter Principle themselves into jobs they hate or suck at.

So instead of creating progressions from Product teams to central teams, I’d favor aggressive rotational policies. By rotating people into and out of those central teams, you ensure that central teams stay attuned to the needs of the Product teams where work is actually getting done. You also remove the career-path issues that often drive top talent to gravitate toward centralization.

Communications and collaboration is another tricky problem. Collaboration is one of the most under-invested capabilities in the organization and my Product team structure is going to make it harder to do well. For areas like analytics, though, it’s critical. Analysts need to communicate practices and learnings across – not just within – product teams. So I’d favor having at least one role (and maybe more) per area in the central team whose sole function is driving cross-team communication and sharing. This is one of those band-aids you slap on an organizational structure because it doesn’t do something important well. Every organizational structure will have at least a few of these.

In an ideal world, that collaboration function would probably always have at least two resource slots – and one of those slots would be rotated across different teams.

My final structure features highly integrated product teams that blend resources across every function needed to deliver a great digital experience. Those teams don’t dissolve and they don’t pass off products. They own not just the creation of a product, but its ongoing improvement. Almost needless to say, analytics (customer, behavioral and attitudinal) is embedded in that team right from the get-go and drives continuous improvement.

Those teams are supported by centralized groups organized by function (IT, Design, Analytics) that handle key support, integration and standardization tasks. These centralized teams are kept as small as is practical. Rotational policies are enforced so that people experience both centralized and product roles. Salary bands are kept very wide and the organization tries hard not to incent people out of roles at which they excel. Included in the centralized teams are roles designed to foster collaboration and communication between functional areas embedded in the product teams.

Finally, support functions like HR and Finance are mostly kept external. However, where compelling reasons exist to incubate them with digital, they are embedded in the central structure.

I won’t pretend this is the one right answer to digital organizational structure. Not only does it leave countless questions unanswered, but I’m sure it has many problems that make it fatally flawed in at least some organizations.

There are no final answers when it comes to organizational design. Every decision is a trade-off and every decision needs to be placed in the context of your organization history, culture and your specific people. That’s why you can’t get the right answer out of a book or a blog.

But if you’re building an incubated digital organization, I think there’s more right than wrong here. I’ve tried to keep the cop-outs and dotted lines to a minimum and focused on designing a structure that really will enable digital excellence. I don’t say deliver it, because that’s always up to the people. But if your Product Managers can’t deliver good digital experiences with this organization, at least you know it’s their fault.

Competitive Advantage and Digital Transformation – Optimizing Retail and eCommerce

In my last posts before the DA Hub, I described the first two parts of an analytics driven digital transformation. The first part covered the foundational activities that help an organization understand digital and think and decide about it intelligently. Things like customer journey, 2-tiered segmentation, a comprehensive VoC system and a unified campaign measurement framework form the core of a great digital organization. Done well, they will transform the way your organization thinks about digital. But, of course, thinking isn’t enough. You don’t build culture by talking but by doing. In the beginning was the deed. That’s why my second post dealt with a whole set of techniques for making analytics a constant part of the organization’s processes. Experimentation driven by a comprehensive analytics-driven testing plan, attribution and mix modelling, analytic reporting, re-survey, and a regular cadence of analytics driven briefings make continuous improvement a reality. If you take this seriously and execute fully on these first two phases, you will be good at digital. That’s a promise.

But as powerful, transformative and important as these first two phases are, they still represent only a fraction of what you can achieve with analytics driven-transformation. The third phase of analytics driven transformation targets areas where analytics changes the way a business operates, prices its products, communicates with and supports its customers.

The third phase of digital transformation is unique. In some ways, it’s easier than the first two phases. It involves much less organization and cultural transformation. If you done those first two phases, you’re already there when it comes to having an analytics culture. On the other hand, in this third phase the analytics projects themselves are often MUCH more complex. This is where we tackle big hard problems. Problems that require big data, advanced statistical analysis, and serious imagination. Well, that’s the fun stuff. Seriously, if you’ve gotten through the first two phases of an analytics transformation successfully, doing the projects in Phase Three is like a taking a victory lap.

There isn’t one single blueprint for the third phase of an analytics driven transformation. The work that gets done in the first two phases is surprisingly similar almost regardless of the industry or specific business. I suppose it’s like laying the foundation for a building. No matter what the building looks like, the concrete block at the bottom is going to look pretty much the same. At this third level, however, we’re above the foundation and what you do will depend mightily on your specific business.

I know that it depends on your business is not much of an answer. As a consultant, it’s not unusual to get caught up in conversations like this:

“So how much would it cost?”

“Well, that depends.”

“What kind of things does it depend on?”

“Well, it depends on how deeply you want to go into it, who you want to have do it, and how you want to get it done.”

All of this is true, of course, but none of it is helpful. I usually try to short-circuit these conversations by presenting a couple of real world alternatives.

I think this is more helpful (though it’s also more dangerous). Similarly, when I present the third phase of an analytics driven transformation I try to make it specific to the business in question. And the more I know about the business, the more pointed, interesting, and – I hope – convincing that third phase is going to look. But if I haven’t spent much time a business, I still customize that third phase by industry – picking out high-level analytics projects that are broadly applicable to everyone in the sector.

That’s what I’m going to try to do here, with the added benefit of picking a couple different industries and showing how the differences play out in this third phase. Do keep in mind, though, that the description of this third phase – unlike that of the first two – is meant to be suggestive only. No real-world third phase (certainly no optimal one) is likely to mirror what I lay out here. It might not even be very close. What’s more, unlike the first phase (at least) which is close-ended (when you’ve done the projects I suggest you’re done with that phase), phase three is open-ended. You never stop doing analytics projects at this level. And that’s a good thing.

For the first example, I decided to start with a classic retail e-commerce view of the world. It’s a sector where we all have, at the very least, a consumer’s understanding of how it works. There are many, many possible projects to choose from, but here are five I often present as a typical starting point.

The first is an analytically driven personalization program. With journey-mapping, 2-tiered segmentation and a robust experimentation program, an enterprise should be a in a good position to drive personalization. Most personalization programs bootstrap themselves by starting with fairly straightforward segmentations (already done) and rule-based personalization decisions targeted to “easy” problems like email offers and returning visitors to the Website. That’s fine. The very best way to build a personalization program is organically – build it by doing it with increasing sophistication in more and more channels and at more and more touchpoints.

Merchandising optimization is another very big opportunity. So much of the merchandising optimization I see is focused on product detail pages. That’s fine as far as it goes, but it misses the much larger opportunity to optimize merchandising on search and aisle pages via analytics. Traditional merchandising folks have been slow to understand how critical moving merchandising upstream is to effective digital performance. This turns out to be analytically both very challenging and very rich.

Assortment optimization (and I might be just as likely to pick pricing or demand signals here) has long been a domain of traditional retail analytics. As such, I have to admit I didn’t think much about it until the last few years. But I’ve come to believe that digital analytics can yield powerful preference information that is typically missing in this analysis. To do effective assortment optimization, you need to understand customer’s potential replacement options. In the offline world, this usually involves making simple guesses based on high-level product sales about which products will be substituted. Using online view data, we can do much, much better. This is a case where digital analytics doesn’t so much replace an existing technique as deepen and enrich it with data heretofore undreamed of. Assortment optimization with digital data gives you highly segmented, localized data about product substitution preferences. It’s a lot better.

I’ve become a strong advocated for a fundamental re-think of loyalty programs based on the idea that surprise-based loyalty with no formal earning system is the future of rewards programs. The advantages of surprise-based loyalty are considerable when stacked up against traditional loyalty programs. You can target rewards where you think they will create lift. You can take advantage of inventory problems or opportunities. You don’t incur ANY financial obligations. You create no customer resentment or class issues. You can scale them and localize them to work with a specially trained staff. And, of course, the biggest bonus of all – you actually create far more impact per dollar spent. Surprise-based loyalty is, inherently, analytic. You can’t really do it any other way. Where it’s an option, it’s always one of the biggest changes you can make in the way your business works.

Finally, I’ve picked digital/store integration as my fifth project for analytics-led transformation. There are a number of different ways to take this. The drives between store and site are complex, important and fruitful. Optimizing those drives should be one of the analytics priorities for any omni-channel retail. And that optimization is a combination of testing and analytics. In this case, however, I’ve chosen to focus on measuring and optimizing digital in-store experiences. You’re surely familiar with endless-aisle retail; where digital is integrated into the in-store experience. The vast majority of these physical-digital experiences have been quite ineffective. Almost always, they’ve been executed from a retail perspective. By which I mean that they’ve been built once, dropped into the store, and left to fail. That’s just not doing it right. In-store experiences are getting more digital. Digital signage is growing rapidly. Physical-digital experiences are increasingly common. But if you want actual competitive advantage out of these experiences, you’d better tackle them from a digital test-and-learn/analytics perspective. Anything less is a prescription for failure.

Digital Transformation Phase III Retail

So here’s my first round of Phase Three projects for an analytics driven transformation in retail. Each is big, complex and hard. They are also important. These are the projects that will truly transform your digital business. They are rubber-meets-the-road stuff that drive competitive advantage. It would be a mistake to try and execute on projects like this without first creating a strong analytics foundation in the organization. You’re chances of misfiring on doing or operationalizing the analytics are simply too great without that foundation. But if you don’t move past the first two phases into analytics like this, you’re missing the big stuff. You can churn out lots of incremental improvement in digital without ever touching projects like these. Those incremental improvements aren’t nothing. They may be valuable enough to justify your time and money. But if that’s all you ever do, you’ll likely find yourself wondering if it was all really worth it. Do any of these projects successfully, and you’ll never ask that question again.

Next week I’ll show a different (non-retail) set of projects and break-down what the differences tell us about how to make analytics a strategic asset.

[Just a reminder that if you’re interested in the U.S. version of the Digital Analytics Hub you can register here!]