Eric D. Brown, D.Sc.

Data Science | Entrepreneurship | ..and sometimes Photography

Category: The New CIO (page 3 of 41)

Digital Transformation – Are CEO’s and CIO’s aligned?

Digital TransformationI just read “Digital transformation will shape 2016” over on and was a a passage caught my eye.

Before I give you the passage, let me put the sentence into context.  The CIO article is discussing a recent IDC report titled ‘IDC FutureScape: Worldside CIO Agenda 2016 Predictions.’ This report provides some predictions on what the CIO and IT  will be focused on for the coming year(s).

The passage that caught my eye was this one:

According to IDC, the biggest issues in IT leadership will center on business needs, capabilities and availability related to digital transformation. The data shows that two-thirds of CEOs plan to focus on digital transformation strategies for 2016 and that CIOs will be major players in leading every department through this shift. In terms of capabilities, only 25 percent of CIOs report feeling confident in how they are driving new digital revenue streams.

Emphasis mine.

When I read that paragraph, I was a bit perplexed as to how two-thirds of CEO’s will be focused on digital transformation and the CIO will a ‘major player’ in leading these initiatives while at the same time only one-quarter of CIO’s felt confident in how they and their teams are driving new digital initiatives and revenue streams.

Now – before anyone skewers me, I do realize that digital transformation is about much more than finding new revenue streams. Digital transformation covers all aspects of the business from finding new revenue streams to reducing costs throughout the business via technology.  CIO’s know how to do the latter…but as we see from the survey, not many of them are confident they can do the former.

If CEO’s are going to be focused on digital transformation in 2016 and CIO’s are going to be one of the leaders of those initiatives, one would think that those CIO’s would be much more confident in their capabilities (and abilities) to drive revenue. Right?

Sure, CIO’s can help to drive digital transformation without ‘knowing’ how they are doing with digital revenue streams, but if I were a CEO, I’d want to know my CIO had a real handle on all things digital, including how digital is driving revenue.  Alternatively, if I were a CIO and I knew the CEO was focusing on digital transformation, I’d be doing everything in my power to make sure I (and my team) were fully up to speed on what we were doing, planning to do and could potentially do in the coming year.

Based on the responses in this survey, I worry that the the CEO and CIO aren’t quite on the same page when it comes to digital transformation going into 2016.

The Benefits of Open Data Within an Organization

Open DataA recent article by Christian McMahon titled “Open Data – How Far Do We Go?” got me thinking about the idea of ‘open data.’  Christian’s article discusses the idea of open data in general where entire data sets are freely available to anyone that wants to access and use that data for whatever reason.

Christian’s idea of open data is a great one and it can be re-defined as an idea that can be used within organizations. The idea of open data can be thought of as making all (or at least most) of an organization’s data available for access and analysis by anyone that needs or wants it.

Open data within an organization isn’t really that far-fetched. With the right data governance and data management systems and processes, a company can make all of their data-sets open to anyone within their organization while keeping security, privacy and access rights in mind.

Making data more open can bring quite a lot of value to an organization. By opening up data to more people, a business can become much ‘smarter’ by way of having more eyes and ‘brains’ focused on various data sets.  Just imagine what you’ll be able to accomplish with hundreds of people looking at data throughout the day rather than just a few data analysts?   What type of insight might be found when people of different backgrounds and experiences have the ability to dig into an organization’s data?

Having more people digging through your data also means less work for the already over-worked data analysts.  The need to continually create new reports and start analytical projects for relatively minor requests will go away if the people asking for those reports and projects have access to the data that they need to review.  Of course, a company will still need professional analysts and data scientists to do much of the heavy lifting with big data but taking an open data approach can add value by freeing up their time.

One additional benefit to the open data approach is that it can democratize the organization by making information and knowledge much more available which can lead to many things including innovation and growth for the business.  You never really know where a new idea will come from so why not make it easy for anyone within the business to analysis data and find new knowledge?

Open data allows organizations to take the fullest advantage of the world of big data.  With the size of data growing inside most organizations today, it just makes sense to open up that data to as many people as possible to give your business the best opportunity for finding those little ‘nuggets’ of knowledge that lead to real innovation.

Is your company approaching your data with an ‘open data’ mindset?

Data Ownership within an Organization

data ownership in an organizationRecently, I was having a conversation with an IT VP about data management, data access, reporting and analytical approaches to the data stored within the organization.  The conversation was a long and frustrating one.

I started working with this company to help them open up access to all their data repositories to allow people within the company to access and analyze the data without having to go to a data analyst to ask for a report or data set.   Everything that I’ve suggested this organization needs is being stonewalled by this particular individual with responses like “that isn’t secure,” “they can’t see that data” and “that isn’t their data.”

After many meetings without any real movement, I decided it was time to bring in the CIO into the discussion to help with either breaking down the walls this person was putting up or to tell me that those walls were staying put regardless of my suggestions.

The CIO, VP and I sat down and began discussing the issues and concerns that the VP had regarding my suggestions.  After we walked through all my suggestions and all the reasons the VP declared that they couldn’t be implemented, the CIO asked a few questions for clarification. After a few minutes of back and forth, the CIO declared to the VP that “we don’t own this data, the business owns this data…find a way to make this happen.”

I thought that was an excellent response from the CIO – “we don’t own this data” is a far cry from most IT professional’s feelings about dat. Many view data as their ‘property’ because they are the ones tasked with storing and protecting it.   That’s not a bad thing…but it has made many within IT feel like they have to say ‘no’ more than they say ‘yes’ to requests.

Through much negotiation and teeth gnashing, the VP and I were able to work through all of my suggestions and develop a plan to implement the necessary systems to reach their objective.  Included in this plan are proper data management and data governance systems and processes along with the right type of analytics engine to allow just about anyone within the organization  to take a look at data that interests them.

The key point of this is to highlight the fact that IT professionals don’t “own” the data. We don’t get to say ‘yes’ or ‘no’ to who gets access and what can be done with that data. We are just the keepers of the data and need to think about systems and processes that allow the organization to use that data in whatever way makes the most sense for the business at any given time.

Today’s Data Challenge is Yesterday’s Data Challenge

ChallengesIf you spend any amount of time reading or talking about big data, you’ll often find that one of the challenges facing an organizations use of big data today is the same as problem that these organizations faced just a few years ago: using the data to actually do something.

Before the popularity of big data, most large organizations were focused on building their ‘knowledge warehouse’ to store data. Using business intelligence tools, these companies would then build out reports for various departments to run. These reports were generally very static (e.g., month-end financial reporting) and rarely did they provide any way for users to dig deeper into the data behind the reports.

The challenge in the ‘old’ days was to get people to look at these reports with a critical eye to using that data to improve the business. Many organizations did a good job at this but the vast majority of companies I’ve worked with and for did not. Most people within these organizations would see these reports, make sure there wasn’t any surprises contained within the reports, consolidate the reports into other reports and then move on. Very rarely did anyone dig any deeper into the data and if they did, they’d assign the additional analysis to an analyst and ask them to find out something didn’t look right.

What I find interesting is that I still see this same approach even within companies that claim to be ‘data driven’.  These companies have exponentially more data than they had just a few years ago, yet they still treat this data (and the analysis of that data) in the same way.  They spent a great deal of money on platforms to collect and analyze data yet the data analysis process remains the same.

The exact same challenge that faced organizations in years past exists today. They have data, analytics and reporting capabilities but rarely dive into the data for anything more than basic static reports. Additionally, the output of the analysis is generally reviewed and then put on a shelf (or deleted) without any real thought into what that analysis means or could mean to their business.

Today’s data challenge is the same challenge that has plague organizations for years. If you don’t use data to truly understand your business and make changes based on the analysis you do, you are wasting precious time and money.  Data (and the analysis of that data) is useless worthless until you actually use it.

This post is brought to you by HP’s Business Value Exchange.

Data is only as good as you make it

data is only as good as you make itI’m currently working with a client who is very immature when it comes to data analysis.  This particular client has no history of analyzing data and barely any history of reporting. Their idea of analysis is looking at a few finance reports to see how the business is doing.

Now, if this particular client was a small business, I’d have no problem with this approach….but they aren’t. They are a multi-million dollar business with multiple departments spread across multiple states. They really should no better – and their CEO said as much to me during our first conversation.

I’ve been working with this client to set up processes to collect, analyze and use data throughout their business. When I started the project, I spoke to the CEO about the need to not only work on data collection and analytics but also the data ‘culture’ within the business.  The agreement was that I would work on the data collection/analysis aspects and the CEO would drive the cultural change needed.  Not ideal but that’s how these projects go sometimes.

According to a conversation I had with the CEO a few weeks ago, the project has been a huge success. The company is now talking about data in ways they never did. Their CEO is constantly looking for additional data to help make better decisions. Data is being incorporated into all aspects of the strategic planning process to try to develop stronger plans for the future.

When I spoke to the CEO last week, I wasn’t a bit surprised to hear him say the following:

Everyone has all the data they will ever need, but nobody is actually using the data!

Apparently, the majority of people within the business love all the data and ‘reports’ but they aren’t actually using that data to make any real changes to their operations. They are viewing the reports and, by all accounts, love to see ‘what is happening’ but they aren’t viewing the data or reporting with a critical eye to making improvements to their business.

This is the ‘data culture’ issue that needs addressing within most organizations.  You can collect and analyze all the data you want but if you don’t use that data for something more than taking up storage space and processing time, you are wasting money and time.

Data is only as good as you make it.

The Dichotomy of Data Access and Data Privacy

yin-yangIn order to use data within your business, you must first collect that data. Seems simple enough right?  You capture some data, store it somewhere and the use that data at a later time in your analysis.

What about data privacy concerns? Where are you collecting your data? How are you protecting that data?  Are you collecting/using social network data or other user-generated data from public sources?   If you are using data from ‘users’, do they know their data is being collected, stored and used for something other than the system it was generated in?

These types of questions are the ones that every organization and data scientist should constantly be asking, especially if a single byte of captured and/or analyzed data is generated by a consumer or user of your systems.

In addition to the data that you might capture within your organization (and perhaps from social media, blogs and other user-generated content), there will be data available from data brokers. It may not be next week or next year, but you can bet that all the data that are captured via wearables and other Internet of Things devices will be made available for a price.

Over on Business Value Exchange, Helen Beckett, in a post titled “Watch Out! The Personal Data Market is Coming”, writes:

Citizens and consumers, who generate thousands of bytes of data every day – switching on devices or utilities, making purchases, boarding transport or just walking down the street in CCTV cities – can celebrate. The data they collectively generate is an asset that is being mined to create value and making companies and even industries rich on the back of it. Now the personal data exchange is coming.

Companies will jump at the chance to buy data from these brokers and exchanges and begin using that data in their analysis. Just think about how powerful it would be for an insurance company to have access to your health data via Apple Health or Fitbit or data from a device in your car that reports on speed, location, distance driven, etc.

From a data science and an organizational perspective, having access to data like this is an enormous advantage for any company looking to better understand their clients.  If you can gather data on individual users daily activities, it makes it much easier to market to those users as well as customize your products/services to those users.

From an individual perspective, it is a little frightening to know that every aspect of my driving or my fitness routines (or lack thereof) could find its way into the hands of my insurance company. Likewise, it is disconcerting to know that said data could also make its way into the hands of companies who want to market their services or products to me based on where I’ve driven or how far (or how little) I’ve walked in the last few weeks.

As data scientists and organizations, we want to be able to access and analyze as much data as possible and we want data that is as granular as possible.  With personal data available today (or available in the near future), we have very granular data.

As individuals, we are (or should be) concerned with how companies are using our own data.  We at least want to know how that data might be used and when it is being used.

This is the dichotomy we face today. We want to use as much data as possible but we also worry about data privacy of our own data.  The challenge for any organization or data scientist is to find the right balance between using the right data with the right granularity with necessary privacy issues that consumers need and want.

How is your organization balancing data privacy and data access?

This post is brought to you by HP’s Business Value Exchange.

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