Data and Culture go hand in hand

data and culture go hand in handA few weeks ago, I spent an afternoon talking to the CEO of a mid-sized services company.  He’s interested in ‘big data’ and is interviewing consultants / companies to help his organization ‘take advantage of their data’.  In preparation for this meeting, I had spent the previous weeks talking to various managers throughout the company to get a good sense of how the organization uses and embraces data.  I wanted to see how well data and culture mixed at this company.

Our conversation started out like they always do in these types of meetings. He started asking me about big data, how big data can help companies and what big data would mean to their organization.  As I always do, I tried to provide a very direct and non-sales focused message to the CEO about the pros/cons of big data, data science and what it means to be a data-informed organization.

This particular CEO stopped me when I started talking about being ‘data-informed’.  He described his organization is being a ‘data-driven company!’ (the exclamation was implied in the forcefulness of his comment).  He then spent the next 15 minutes describing his organization’s embracing of data. He described how they’ve been using data for years to make decisions and that he’d put his organization up against any other when it comes to being data-driven.  He showed me sales literature that touts their data-driven culture and described how they were one of the first companies in their space to really use data to drive their business.

After this CEO finished exclaiming the virtues of his data-driven organization, I made the following comment (paraphrasing of course…but this is the gist of the comment):

“You say this is a data-driven organization…but the culture of this organization is not one that I would call data-driven at all.   Every one of your managers tells me most decisions in the organization are made by ‘gut feel’.  They tell me that data is everywhere and is used in making decisions but only after the decision has been made.   Data is used to support a decision rather than informing the decisions. There’s a big difference between that and being a data-informed and a being a data-driven organization.

After what felt like much more than the few seconds it was, the CEO smiled and asked me to help him understand ‘just what in the hell I was talking about’.

What am I talking about?

I’m talking about the need to view data as more than just a supporting actor in the theatrical play that is your business.  Data must go hand-in-hand with every initiative your organization undertakes.   There’s some folks out there that argue that you need to build a data-driven culture, but that’s a hard thing to sell to most people and simply because they don’t really understand what a ‘data-driven’ culture is.

So…what is a ‘data-driven culture’?  If you ask 34 experts on the subject, you’ll get 34 different explanations.  I suspect if you ask another 100 experts, you’ll get 100 additional answers.  Rather than trying to be a data-driven culture, its much better to integrate the idea of data into every aspect of your culture. Rather than try to create a new culture that nobody really understands (or can define), work on tweaking the culture you have to be one that embraces data and the intelligent use of data.

This is what happens when you become start moving toward being a data-informed organization.   Rather than using data to provide reasons for the decisions that you make, you need to incorporate data into your decision making process. Data needs to be used by your people (an important point…don’t forget about the people) to make decisions. Data needs to be a part of every activity in the organization and it needs to be available to be used by anyone within the organization. This is where a good data governance / data management system/process comes into play.

During my meeting with the CEO, I spent about 2 hours walking through the topics of data and culture.  We touched on many different topics in our conversation but always seemed to come back around to him not understanding how his organization isn’t “data-driven”.  He truly believed that he was doing the right things that a company needs to do to be ‘data-driven’. I couldn’t argue that he wasn’t doing the right things but I did point out the fact that data was considered as an afterthought in every conversation I had with his leadership team.

Data and culture go hand in hand

Since that meeting, the CEO has called me a few times and we’ve talked through some plans for helping bring data to the forefront of his organization.  This type of work is quite different than the ‘big data’ work that the CEO had original wanted to talk about.  There’s no reason not to continue down the path of implementing the right systems, processes and people to build a great data science team within the company, but to get the most from this work, its best to also take a stab at tweaking your culture to ensure data is embraced and not just tolerated.

A culture that embraces data is one that ensures data is available from the CEO down to the most junior of employees.  This requires not only cultural change but also systematic changes to ensure you have proper data governance and data management in place.

Data science, big data and the whole world that those worlds entail is much more than just something you install and use.  Its a shift from a culture focused on making decisions by gut-feel and using data to back that decision up to one that intuitively uses data throughout the decision making process, including starting with data to find new factors to make decisions on.

What about your organization? Does data and culture go hand in hand or are you trying to force data into a culture that doesn’t understand or embrace it?

Be pragmatic, not dogmatic

be pragmatic, not dogmaticI’m currently reading Scott Brinker’s book Hacking Marketing: Agile Practices to Make Marketing Smarter, Faster, and More Innovative (awesome book – look for a much more complete review here soon) and came across a line in Chapter 7 that says “Be pragmatic, not dogmatic.”

This really spoke to me.

One of the things I dislike about many business books is that they try to create dogma and that readers should follow their ‘recipe’ and you’re business will be ‘great’.  Much like Isaac Sacolick’s Driving Digital (see my review of Isaac’s book here), Scott doesn’t do that with his book…instead he’s telling people to stop trying to find a recipe that other companies have used for success and start from scratch (with lessons learned from others of course).

One of the most damaging routes a company can take is trying to mimic another. I’ve been in meetings listening to product managers describe their product roadmap that contains 99% ‘me too’ features to keep up with their competitors.  When I ask about innovation, I get blank stares.  These folks are stuck in the dogma of their industry and their organization. They are focused on imitation rather than innovation.

That’s where being pragmatic comes into play. Sure…there may be features that you must have to compete in your vertical/industry but if you’re entire roadmap is focused on imitation, its time to take a step back and rethink your approach, your investment and your business. Rather than mimic everything others are doing (e.g., being dogmatic), take a the pragmatic approach.  Take a look at what your competitors are doing, what your clients want, what you can deliver and what best fits into your organization’s long-term goals and then do that.

Another aspect of pragmatic vs dogmatic that I see often is that of project management. How many times have you heard (or said!) “well…we need to build a gantt chart before the project can start” or “that’s not how the PMBOK” says to do it or ‘Scrum requires us to do X, Y and Z in that order.”   That’s dogmatic.  Not every project requires a gantt chart or a daily 15min standup meeting. Not every organization can (or should) follow the dogma of project management methods.  The most successful project managers out there are those that know when to follow guidelines and when to deviate from said guidelines.

So…be pragmatic, not dogmatic.  Thanks for the quote Scott.

Your data project is going to fail

Your data project is going to failI hate to be the bearer of bad news….but your data project is going to fail.

Maybe not the one you’re working on today. Maybe not the one you’re starting next month. Heck, maybe not the one you don’t even know about yet…but at some point in the future – if you stay in the data world long enough – your data project is going to fail.

There are may ways your data project could fail. Martin Goodson shares his thoughts on Ten Ways your project could fail, and I’ve seen failure’s driven by each of Martin’s “ten ways” during my career. The most spectacular failures have come from the lack of clear strategy for any data projects.

It should be common sense in the business world that if you don’t have a strategy and plan to execute that strategy in place, you are going to have a hard time. When I use the word ‘strategy’, I don’t just mean some over-arching plan that somebody has written up because they think ‘data is the new oil‘ and by ‘doing’ data projects they’ll somehow magically make the business bigger / better / richer / strong /etc.

Data projects are just like any other project. Imagine you need to move your data center…you wouldn’t just start unplugging servers and loading them into your car to drive to the new data center, would you?

Would you go and spend $20 million to hire a brand new sales team without building a thorough strategic plan for how that sales team will do what they need to do?  You wouldn’t hire the people, on-board them and then say ‘start making phone calls’ without planning sales territories, building ‘go to market’ plans and building other tactical plans to outline how the team will execute on your strategy would you?  Scratch that…I know some companies that have done that (and they failed miserably).

Data projects require just as much strategic thinking and planning as any other type of project. Just because your CEO (or CIO or CMO or …) read an article about machine learning doesn’t mean you should run out and start spending money on machine learning. Most of you are probably nodding along with me. I can hear you thinking “this is common sense….tell me something I don’t know.”  But let me tell you…in my experience, it isn’t common sense because I see it happen all the time with my clients.

So we agree that if you don’t have a strategy, your data project is going to fail, right? Does that mean if you do the strategic planning process correctly, you’ll be swimming in the deep end of data success in the future? Maybe. Maybe not. The strategic plan isn’t everything. If you were successful because you planned well, then every company that ever hired McKinsey would be #1 in their industry with no hope of ever being surpassed by their competitors.

After you’ve spent some time on the strategy of your data project(s), you’ve got to spend time on the execution phase of your project.  This is where having the right people, the right systems / technologies in place to ‘do’ the data work comes into play.  Again, every one of you is probably nodding right now and thinking something like “sure you need those things!”  But this is another area that companies fall down time and time again. They kick off data projects without having the right people analyzing the data and the right people / systems supporting the projects.

Take a look at Martin’s “Ten Ways” again, specifically #3.  I watched a project get derailed because the VP of IT wouldn’t approve the installation of R Studio and other tools onto each of the team member’s computers.  That team spent three weeks waiting to get the necessary tools installed on their machines before they could get started diving into any data.  This is an extreme case of course, but things like this happen regularly in my experience.

Hiring the best people and building / buying the best systems aren’t enough either. You need to have a good ‘data culture’, meaning you have to have people that understand data, understand how to use data. Additionally, your organization needs to understand the dichotomy of data – it is both important and not important at the same time.     Yes data is important and yes data projects are important, but without all the other things combined (people, strategy, systems, process, etc), data is just data.  Data is meaningless unless you convert it to information (and then convert it yet again into knowledge).  To convert data, you need a company culture that allows people the freedom to ‘convert’ data into information / knowledge.

So…you think you have the best strategy, people, systems, process and culture, yes?  You think you’ve done everything right and your data projects are set up for success. I hate to tell you, but your data project is going to fail. If you have the right strategy, people, systems, process and culture in place, you aren’t guaranteed success but you will be in a much better position to recover from that failure.

Can you really win if you aren’t the best?

Can you really win if you aren’t the best?People often say that if you work hard and apply yourself, you’ll succeed. But lets be realistic….that isn’t always true, especially because everybody has a different definition of ‘succeed.’   Sure, you can work hard and apply yourself and become better than you were, but it doesn’t mean you’ll become the ‘best’ at something.  That’s just not how life works.

Let’s say, for example, that you decide to become the world’s fastest runner in the 100m race. That’s a lofty goal, but unless you are born with a very specific set of genes and start training very young, the probability of meeting that goal is pretty low.  That said, there’s nothing stopping you from pushing yourself to become faster than you were yesterday or last week.

If you aren’t the ‘best’ at something, does that mean you can’t win at that something (or at life)? Not at all. Even the absolute best have bad days.  Underdogs win all the time, which is why you should always continue to improve and become better than you were because you never know when your chance might come to be ready when the ‘best’ falters.

If you’ve not seen or read Moneyball (the book is here, the movie is here), you are missing out. The book talks about how the Oakland A’s baseball organization took the ‘B’ players and built a baseball franchise around them.  I don’t recall if there were any of baseball’s “best” players on the Oakland team at the time, but I do recall that there were a lot of the ‘also rans’ that many teams didn’t think were good enough for their team.

Many people will argue that the real story behind Moneyball is how statistics and data analysis can play a really important role in running a business. These people are correct…these things are important and they were an important part of the Moneyball / Oakland A’s story, but the part of the story that many miss is that these ‘B’ players also worked really hard to become better at what they did.  They didn’t just relegate themselves to be also-rans…they kept pushing harder and harder to become better than they were.

The same is true for corporations.  Maybe you don’t have a team comprised of the most talented and skilled employees, but if you and your leadership team continue to push yourselves and your people, you (and they) can do wonderful things.  If you build a culture of improvement where the smallest failures aren’t punished and show your team(s) that you are constantly improving yourself – and expect the same from them – your team and company will be able to compete. You may not win every time, but you’ll be around for the long-haul.

You can win if you aren’t the best. Anyone can. You may never be considered the best, but if you continue to try to get better, you’ll always be better than you were.

That said, just imagine if you don’t push yourself or your team to constantly improve? If you and your team are OK with being average, you’ll never have the chance to win.

Innovation needs process change

change aheadJeffrey Philips currently wrote a nice piece titled “Innovate your processes before innovating your products” over on his excellent Innovate on Purpose blog. In that article, Jeffrey argues that before a company can innovate its products/services, it must innovate its processes if it hopes to build a sustainable edge via innovation over its competition.

When I read Jeffrey’s post, I found myself nodding at everything he wrote. While the need to focus on innovation in your product / service line is a real one, many organizations completely miss the need to look at process change to support these innovations.

Jeffrey provides a good example in his article on why process change is needed. He writes:

..most product development processes do a poor job allocating resources and establishing priorities, and are bogged down with poorly defined projects and inadequate staffing levels.  It’s exceptionally rare for products to exit the process on time and on budget.

Anyone that has been involved in an type of project management or product management role will immediately agree with the above statement. Heck..anyone in IT will immediately agree with this statement.   There’s never enough people or resources to do everything, yet it feels like everyone is asked to do everything…and do it now.

In addition to the resource issue, there are many organizations with outdated and ill-informed processes for getting things done.

I recall an IT group in the not too distant past (we are talking 2008-2009 time-frame) that required a change request to be manually filled out with pen/paper and then handed to a secretary. This secretary would then take the change request form around to get signatures from the necessary people and then FAX the change request to the change management team.  Mind you…this team was located in the same building, yet they required a faxed copy of the change request.

The above example might seem like an outlier (and maybe it is) but I’ve run across many outliers like this in my career. Companies are so focused on the new and innovative that they forget to look internally at their own processes.

In order to truly innovate your product and/or service line, you need to look at your own processes first. It may not be as ‘sexy’ as building that new product, but its just as important (or maybe even more important) than that new product.

Back to the example I provided earlier. That company could not have delivered an innovative product or service and sustained that product/service.. In fact, they tried a few different things and even started an ‘innovation group’ to focus on innovation but the majority of ideas that came from this group where stonewalled by the arcane processes found within the company. It wasn’t just the IT group that had out of date processes…every part of the organization needed to have some process re-engineering done. Ultimately, this organization had to step back and rethink many of their internal and back-end processes before they could focus on innovation.

Processes are the lifeblood of an organization. If you don’t step back and take a look at your processes, your innovative ideas might just suffer.

…and then what?

...and then what?I just finished reading a great article titled “The Most Important Question You Can Ask: Then What?

In the article, the author writes:

The great art of life is in balancing the short term and the long term, so that one can have enjoyment with integrity – pleasure with purpose. But in most areas of life, we pay strict attention to the immediate consequences of things. We look at the immediate results of a social or economic policy and call it a victory (or a complete failure).

The solution to  ‘short term’ thinking, according to the author, is to ask “…and then what?”.  By asking this simple question, we can force ourselves to look past the immediate and into the longer term. The author writes:

The problem is that so few of us take the effort to do this very simple thing. It’s understandable, we get caught up in the moment, and we don’t particularly enjoy thinking in minute detail each and every moment of our lives. But in the coming era, it will become increasingly important for us to ask these kinds of things, as our interconnectedness makes ideas and new technologies spread faster than ever before.

This very simple step of asking “…and then what?” can make a huge difference to any individual’s or organization’s planning process. By thinking about the step after the step, you’ll be able to open up plans to include much more than just the things needed to get the current project complete.

A perfect example of the lack of asking “…and then what?” can be found with most instances of the phenomenon known as Shadow IT.  Shadow IT usually arises because the IT organization can’t/won’t give a person/group a technology/system that they think they need. This group then goes out and finds something to fill their immediate need without thinking ahead. What will happen when the data in that new system needs to be integrated with other company systems, needs to be backed up or you need to move it to another cloud service provider? These are all very simple scenarios that can be covered if you simply ask “…and then what?”

Are you and your organization asking yourselves “…and then what?” during your planning?

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