As the concept of becoming data driven embeds more and more into business operations, and more and more information systems are brought online, one of the central questions which is asked by CEO’s and executives across the world is - ‘What kind of person, team or contractor should we employ to achieve what we need?’

Getting the right people involved in data driven business is the primary issue of the decade, with businesses rising and falling on the quality, diversity and integrity of those they entrust with their data.

In this post I want to share my observations on what I believe to be the top five defining characteristics of excellent Data Driven Teams. Teams of this nature create enormous competitive advantage for their organisations, finding new ways to increase efficiency and delivering decision quality information to decision makers. As a side benefit, they are often able to help businesses execute quickly on new market opportunities, creating a positive feedback cycle for all involved.

Getting the right people involved in data driven business is the primary issue of the decade!

​#1 Passionate About the Business
Every single successful analytics team I’ve ever met has exhibited this characteristic. It’s not just about the way they dress or talk, or the lunches they have or perks they enjoy - there’s a buzz around them. When you hear them talk about their company and the intimate details about how the organisation works and how they found this AMAZING insight when they combined some different data sources, you walk away feeling inspired.

A great example of this is a post I recently read by the Air BnB team, talking about migrating their data. I’m not going to expand on the details of what they did (although it was impressive) but what I noticed is how passionate they were about their organisation. I could feel the excitement of the challenge oozing out of them, leaping out from the page. Yes, there was some technical details in the post, and yes, the challenge they faced was significant, but it was clear that they loved what they were doing and were determined to succeed.

This kind of passion is what separates organisations who do data because they’ve been told what a great idea it is from those organisations which see the transformational benefits it brings. For me, I was so inspired by the Air BnB post I actually applied for a job there!
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#2 Know technology
The second defining characteristic of an excellent Data Driven Team is a fundamental commitment to becoming technical experts in their field. This is critical.

The Information Age is fast gathering pace, and every day there are new methods being released to market. Even over the past couple of years there has been the rise of No SQL database infrastructure, the introduction of Meteor, a continuing development in the thoughts and principles of REST based web access, big data analytics like Hadoop and so on. This is not to mention the incredible developments in cybersecurity including user behaviour analysis, encryption and the growing rise of mobile interaction.

For many organisations this constant barrage of technologies appears to be simply a very expensive and continuing hobby for a group of people who like doing interesting things with computers. In truth, each of these new technologies, architectures, ideas and concepts come with their own advantages and disadvantages and an excellent Data Driven Team will be able to explain this.

As time goes on, this defining characteristic will be clearly felt across the organisation as information becomes more timely, more accurate and more in depth. It will revolutionise the way you see data and create depth to your activity.

#3 Exercise Leadership at All Levels
Leadership is defined by John C Maxwell as 

Leadership is not about titles, positions or flowcharts. It is about one life influencing another.

It is this ability to influence those around which is a defining characteristic of excellent Data Driven Teams. As organisations build effective informations systems and begin to dive deep into what it’s telling them, there comes a point where the data needs to be translated from geek language into decision maker language. Only excellent data analysts and scientists can make this link, figuring out the most effective graphs, plots and emails to send to the right people.

It goes deeper than this though. Understanding the right data almost invariably leads to tradeoffs between efficiency and effectiveness, often related to timeliness. Due to the nature of data analytics, these tradeoffs typically exist in the realm of extremely technical details, which means that only technical experts can really make a decision. 

When this defining characteristic is missing, teams become paralysed by inaction and unable to present their case to the organisation for further action. The impact of this will not be felt immediately, but over time information quality will diminish and the usefulness of the analytics team to building competitive advantage will disappear.

#4 Able to Focus on the Big Picture
Many IT teams attempt to solve every individual issue on a case by case basis, never taking the time to look at the broader issues being raised. As a result, the teams end up with an increasing burden of supportability for individual solutions, effectively parcelling out their time on issues which of only minimal benefit to the broader organisations. 

In contrast, one of the defining characteristics of excellent Data Driven Teams is the ability to contribute to the larger organisational goals. This means being able to assess the distinction between smaller issues with large implications and larger issues which have individual implications. Excellent teams often spend a lot of their time on whiteboards and in meeting rooms plotting data flows and implications, circling back to users and how to provide analytics - but always with the larger picture in mind. As a consequence the entire organisation benefits as information flows are streamlined and analytics steadily improved. 

Ironically, when this is done correctly, the change within the organisation so subtle it’s often missed. Individuals end up happier and more motivated as they are being provided relevant data and decision makers at all levels feel more supported by the data they are being given - but often the actual Data Driven Teams fade into the background. Long term the organisation will streak ahead of the competition, creating an almost unbeatable competitive advantage.

#5 Team Players
Finally, excellent Data Driven Teams are defined by their ability to play as a team within a larger organisation. They are generally the first to get involved in a new idea or brainstorm, looking at ways to help, rather than hinder. They seek opportunities to get involved in departments and with staff so they can better understand requirements. And most importantly of all they realise that in many cases they are only one aspect of the broader organisation.

These kind of teams are an absolute pleasure to work with. They get the point. They want to help. They are incredibly invested in the organisation and they really want the company to succeed. For the organisation, it’s of huge benefit as they find new and better ways to improve information flows and analysis, providing a continuing competitive advantage. Returning to my example of the Air BnB data team, these kinds of teams are there to serve their organisation and take the abstract and mundane and make it amazingly relevant. 

Conclusion
The end result of these defining characteristics are teams who provide incredible benefit to their organisation. They understand the business and care deeply about it, working hard help it succeed and grow. As new technologies come in they will continue to grow their organisations data driven capabilities and create enormous competitive advantage.

Take the time to invest in building your team, as they will become your single greatest advantage in a fast moving time in history!!!

As always, if you like what I'm saying add me on social media - I'd love to hear your comments!

As the Information Age continues to gather pace, there’s three terms which continue to pop up about becoming data driven:

1. Business Intelligence. Also referred to as Business analytics.
2. Analytics. Covering the areas of predictive analytics, proscriptive analytics, big data analytics.
3. Information Management. 

These three areas are generally presented as three separate capabilities, each offering something the other areas can’t. This perception is reinforced as the companies offering these services continue to try to differentiate themselves by coming up with all sorts of creative names and descriptions. To make things even more confusing, there’s hundreds of different technical terms which get thrown in - things like Hadoop clusters, test driven development, responsive design and my favourite architecturally driven dissemination (whatever that means).

The result of all these words getting thrown around? Key decision makers who know the exact effect they want have no way of deciphering the noise to see if the method being proposed will give them this result. 

In this post, I’m going to offer my perspective on these terms and explore the central question: Is this method going to give me the effect I need?

The Endstate: Competitive Advantage
It doesn’t really matter if you’re a not for profit, government organisation or good old profit driven enterprise, the entire purpose of organisations is to deliver lasting value to key stakeholders. It follows, then, that the entire purpose of becoming data driven is to allow your organisation to create a competitive advantage through the capture, analysis and dissemination of relevant data across your organisation. In my mind, I define this as:​

And that’s where it really starts. There’s actually no point in investing in becoming data driven if there’s no competitive advantage to be gained. Furthermore, unless an organisation invests in becoming data driven with an understanding that this the greatest competitive advantage to be had, there will not be the will to go through what can often be an uncomfortable change process.

With this in mind, I present a picture on how these terms all relate:

Information Management.
Starting at the base of the triangle, I’ll tackle Information Management first. In a previous post, I go into detail about some of the aspects of what information management is, but in the context of this discussion, I’d like to add some thoughts.

Put simply, Information Management is really the delivery, when and how mechanism of being data driven. There’s plenty of different terms and methods relating to this, and the companies selling this stuff will often talk at length about their Operating Systems, Hadoop clusters, storage solutions and why their technical solution is better than the oppositions. One day I'll write about some of my experience in this area, but it's key to understand that regardless of using Red Hat, Windows Server, SQL Storage or No SQL storage you're still ultimately building the pipes which connect an organisation.

It’s for this reason that Information Management is at the base of the triangle. The first challenge for any organisation is to figure out what on earth they’re trying to track (data), who needs what (information) and how to get it there (management). Understanding this flow and then enhancing it will literally change how you do business!!!


Analytics
The natural desire once data is being gathered and information is being passed around, is to start analysing the day to day transactional nature of things to see what deeper insight can be gathered. There’s a fair bit of art and science which goes into this analysis, but really, from an effects perspective, analytics can be defined as:

This is where all the branches of analytics spring from. All the different methods which get mentioned in sales pitches are really about trying to give decision makers quality information about what is happening, relieving them and their staff of the burden of gathering this information themselves and it’s something I’ve written about in previous posts.

However there’s some pretty important intricacies about analytics which often get missed. 
Firstly, analytics requires a pretty equal split between data scientists and operationally focused individuals. It’s imperative that any solution is developed in tandem with an organisations culture and decision making process. 
Secondly, analytics is never ending (at this stage). It seems that the deeper you go into analytics, the more you realise that you’re just scratching the surface. For instance, in my latest work, I and a team of five individuals are tracking user interactions with data to start speeding up how quickly this information gets given to them. I’ll go into this in a later post, but in this instance, my team and I are actually developing analytics upon analytics, with predicted massive increases in efficiency. The take away point about this is there’s no such thing as a one off purchase in this area.


Business Intelligence
As the top part of the triangle, business intelligence spans the point at which analytics is fed through to decision makers. It requires an effective information system combined with quality analytics and will take a while to get going.

Theres a few points I’d like to make here about business intelligence.

1. All. Business intelligence is exponentially more useful when it is designed to be given to all decision makers, not just executives. When each member of a company is given access to a broader understanding of their roles and how they are being measured, it’s amazing to see the results.
2. It requires an information system. Often companies selling products make out that if you simply lay their analytics on top of existing information systems you’ll come out with some good insights. In reality this is almost never the case. Unless you have systems capable of delivering pipes of information around the organisation, including data warehousing, replication, error checking, web servers, machine learning and so on, your systems will be ineffective at best and at worst actually cripple your people. Take time to see the larger picture.
3. Define what is the ‘right’ information. It’s a simple facet of management, but often missed. Business intelligence is only useful when it is providing decision quality information and for this to happen, it is critical that this is defined for each position.

Does this method give the effect required?
Hopefully by now a method of assessing how effectively you manage your data is being drawn out, along with a framework for building your own capabilities. Here’s a few questions I typically work through with any team I’m involved with to continue to build this framework.

1. What are we trying to achieve? Is it process change, a new market analysis, or tracking of performance?
2. Who needs this information?
3. How is information currently being gathered?
4. Where is analysis currently being done? (it’s almost always in Excel)
5. Why is this information important?

As these questions are answered, it should become pretty clear what needs to happen next. If you have a solid information and analytics team working for you, the rest should start to shake out. If not, please drop me a line as I’d love to help!!!


Conclusion
To wrap up today, I’d like to take the time to encourage you if you’re on this journey. The Information Age transformation has just begun and it’s only gathering pace. Mastering the three areas discussed in this article will take time and be a hard journey, but it’s worth it when you start to see what can be discovered about your organisation! 

​James

The definition of an Epic Business
Epic businesses create lasting value for owners (shareholders), influencing their employees, communities and environment for good. It’s a huge challenge yet endlessly rewarding - something truly worth living for!!!

There’s a whole ton of stuff which goes into creating epic business. It starts with leadership (favourite author: John C Maxwell) and flows right into ethics, purpose, vision and process. Once you hit the practical side of things, you need excellent capital allocation, worthwhile returns on capital and ways of tracking relevant performance metrics - all supported by a management team who can create a highly motivated, passionate workforce.
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Todays post is my argument that without epic analytics it’s impossible to build epic business!!!

Epic performance metrics
I’ll start with everyones favourite part of work: performance measurement - aka KPI’s, Bonus Indicators, What My Boss Rakes Me Over the Coals With or All Management Really Cares About.

There’s a bunch of research about how important tracking performance metrics is. Many management courses teach the theory and meaning of performance metrics, but the reality is getting this right creates incentive for people to come to work and means that everyone is pulling in the same direction. One leader of an epic company had this to say:
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Here’s the thing: Only an epic analytics team can make this possible!!!
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As the Information Age gathers momentum, the speed at which business is conducted, combined with the nature of decision points being tracked results in enormous quantities of data pouring into information systems. All this data has to be analysed, considered, tested and turned into information - and getting this right is a combination of art, science and a touch of intuitive magic.
An epic analytics team gets this. They get the business, get the leaders intent and know how to take this river of data and transform it into a stream of useful information. Working with the IM team, they will build an analytics capability which will provide the kind of metrics most people can only dream about. All of sudden a business transforms into being data driven, changing everything!!!

​Epic capital allocation
Within the world of value investing, championed by the legendary Warren Buffett, one of the greatest ways to create value for business owners (shareholders) is through effective capital allocation. 

Capital allocation refers to the manner in which capital is invested on behalf of a company to build margins. The margins part is critical, because capital allocation is not just about increasing revenue - it can be as much about reducing costs or figuring out how improve processes as anything else. 

Epic analytics in this area is crucial to creating epic businesses. One of the most profit destroying issues within organisations are the hidden costs of doing business, and it takes epic data analysis to figure out where and what they are. Once these hidden costs have been discovered, capital can be invested to eliminate this waste, creating value for owners. This process can take months or years and uncover all sorts of challenging issues - but the result is transformative. Capital allocation becomes exponentially more effective, with the flow on effect of freeing up more and more capital for other projects.
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Epic employee motivation
Pretty much every leadership book ever has one point - motivating those around to achieve the goal. Epic CEO’s and founders are renowned for being able to motivate individuals and create motivating work spaces. 

It’s interesting then to note that there’s a huge amount of research which shows that employees are most motivated when there is a clear link between an organisations values and their own - known as value driven organisations. It's even more interesting to note that one of the factors which comes up when this is discussed is employees desires that their performance be tracked and results mapped out - for instance in this article 'Values Driven Performance: Seven Strategies for Delivering Profit With Principles'

So here’s the thing - linking values to outcomes requires understanding what indicators drive these values and which measures of success need to be tracked. Planning on positively impacting a community for the long run? Define positive. Show employees what that means. Want to create products which change the world for good? Show me what you need to achieve to get there, per person, per day.

These are the kind of questions epic data analysis provides answers too. And if this capability is missing, it’s going to be impossible to get there!

Epic analytics
And so it is that I reach the point of this post. Epic business requires epic data analytics. 

Data analytics forms the glue which binds organisations together to pull in one direction. It dives into the data and begins to tease apart the questions of why and how and who and when and what. It gets involved in an organisation and brings insight, understanding and resolution. Data analytics allows you and every person who works for you to understand the same story and reasons and work together to fix them - testing, assessing and adjusting each step of the way as you see the results unfold.

For this reason, I submit to you - reader, CEO, CFO, CIO that you need data analytics.

James