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.

Big Data + Big Analytics = Big Insights

Big Data + Big Analytics = Big InsightsIn “Big Data, Big Analytics and You”, I wrote:

“Big data is obviously important to most organizations. There’s plenty of data out there and even more data being generated every day. But big analytics is just as important. Without the ability to analyze the data you have at the speed and scale it is being generated, your organization will never really be able to fully take advantage of big data.”

I wanted to follow up that post with another that talks a bit more about the importance of analytics and converting data into actionable insight.

If you ask business executives if they’d prefer more data or more insight into their business, most would (and should) say that they want and need more insight into their businesses. Some people might argue that in order to get more insight, you need more data but in my experiences this is far from true.

More isn’t always better. More data doesn’t deliver more insight. Businesses do not need more data, they need to be able to use data better. Once an organization figures out how to analyze data more effectively to gain the insights they need, only then will more data make a difference.

Data itself is interesting but useless until you do something to find and understand the ‘signals’ contained within. Until you convert your data into information you have nothing of value. Until this conversion happens, you’ve done nothing but waste money on collecting and storing a whole lot of nothing.

In order to turn this ‘nothing’ into something, companies must find ways to turn find the signal within the enormous amounts of data. This signal will then lead to gaining information, knowledge and, ultimately, wisdom. This is where ‘big analytics’ comes into play because in order to truly find value in big data, you must analyze that data at scale. Sure, you can use excel or some other simple approach to try to dig through your data but excel won’t cut it for the large amounts of data that most organizations need to analyze.

Companies need to analyze at scale to find the insights that their executives need and want. This requires the right analytics tools and systems, the right people with the right skills and a culture that allows people to dig into whatever data they feel is necessary to find answers (and new questions).

Neither big data nor big analytics is the answer to today’s business problems but they are the start to finding many answers that a business needs to find as well as finding some questions that organizations didn’t know they had. It won’t be easy and it can be expensive, but if you are truly looking for insights into your business, there’s no better way to find those insights than by combining a good big data strategy with a good big analytics strategy.

Big data and big analytics can provide big insights for any organization willing to put the time and effort into building a big analytics practice.

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

Is Big Data Worth It?

it-isnt-eat-but-its-worth-itI just read an article titled “Marketers: Is Big Data Worth It?

In the article, the author, Larisa Bedgood, does a very good job of addressing the question of whether big data is important for organizations to focus on.  The author rites that:

The moral of the story? It’s about the data, or rather the insights derived from the data. It’s not enough to simply collect the data. Your data must tell a story. Stories of who your customers are, what your competitors are doing, what offers will be most appealing to prospects, which cross-sell and up-sell opportunities you should offer, and so on.

So true.

Big data is indeed worth it as long as you approach the collection, storage, analysis and use of data in the right way. Your data must tell a story but you must be willing to have that story write itself rather than forcing the story along the lines you want it to go.

If you are ‘doing’ big data the right way, you’ll often find more questions than answers, but that’s what makes big data ‘worth it’. With big data, you aren’t just going through the motions…you have to truly put the effort in to find the real value within your data.

Is bit data worth it? Absolutely…but only if you put the time and effort into the analysis of that data. Big data isn’t easy, but it is worth it.

Don’t Ask if you Can’t Act

Don't Ask if You Can't DoIn a recent Harvard Business Review article titled “Don’t Ask for New Ideas If You’re Not Ready to Act on Them”, Ron Ashkenas provides an example of a company wanting to do the ‘right’ thing but not having the processes or systems in place to pull it off.

The example provided by Ashkenas is one that I’ve heard and experienced many times myself.  One of his clients implemented a ‘crowdsourcing’ approach to gathering innovation ideas from people throughout their business. This company received so many responses that it took nearly a month for all of the responses to be analyzed, categorized and reviewed.  It then took a few more weeks for executives to respond to everyone and announce that they were planning on following up on specific ideas to pursue.

As I mentioned earlier, I’ve seen this type of thing happen at other organizations I’ve worked at. The urge to identify and implement innovative ideas is a strong driving force for any organization and crowdsourcing these ideas makes a great deal of sense. That said, taking the step of asking for new ideas is pointless if your organization can’t quickly act upon those ideas.

This is why every organization needs to reimagine (or reinvent) itself as an agile organization. To truly be able to act upon innovative ideas, an organization needs to be able to marshal the necessary resources (e.g., people, systems, data, etc) to be able to analyze and act upon these new ideas.

Organizations need to be able to pivot and turn quickly to address their clients needs and their competitors offerings. This agility requires the utmost agility in all aspects of the business, including the IT group.  The IT group must provide systems and capabilities to allow the business to gather data, analyze that data and act upon that data quickly and easily.

In the example given by Ashkenas, an agile organization with an agile IT group should be able to put the right tools together capture, track, analyze and report on ideas from around the business.  If your IT group can’t put together the right tools at the right time to deliver the right services, you probably need to spend some time rethinking your IT group and its leadership. Additionally, if your IT group can deliver the right tools at the right time but it still takes you weeks or months to analyze and react…you have larger problems than just a non-agile IT group.

Opening Up Your Data

Open-Data1Data and data analytics have been an important part of organizations for many years. Companies have had data warehouses for as long as I can remember. Those data warehouses were generally well designed and well managed and was the final destination of most of an company’s structured data.

Using the data stored within these warehouses, IT professionals and a select few data or business analysts could generate reports and graphs for the organization to manage the business.

There’s a fairly large problem with this approach though. If a report needs to be changed, there’s usually some sort of ‘change’ request that must be made to the IT group to make the change. That change process might be fairly involved or it might be simple and quick but regardless, it adds time and additional people into simple request to ‘view’ data differently.

For this reason, organizations began looking for new visualization tools to allow easier, interactive analysis of data. Thankfully, there’ve been many vendors step up and provide outstanding visualization and interactive analytics solutions.

We still have a bit of a problem though, at least in some organizations. These visualization and interactive analytics tools were restricted to the same staff and processes as before. Requests still need to be made to IT or to a ‘specialist’ to make a change.

That said, we are starting to see some progress towards opening up data and analysis in some organizations with the help of analytics’ software vendors.

Take, for example, the use of SAS Visual Analytics by a group of hospitals in the Netherlands. Their use of SAS’ product allows their employees to review, analyze and report on data without the need to go to IT or a data analyst to make a request to add a report or get access to a data set.     Rik Eding, a data specialist at one of the hospitals, had this to say about their use of an interactive analytics and visualization platform:

“Analytics is no longer just for our finance department or data analyst … SAS Visual Analytics literally puts the power of analytics into the hands of employees, yielding invaluable results.

Platforms like this allow organizations to put the data into the hands of the people closest to the ‘problem’ they are trying to solve. Rather than allowing these employees access to a few reports and hoping it provides the information they need, interactive analytics platforms allows those users with the most data and problem context to dig into the data and try to find solutions to their problems.

Beyond getting the data into the hands of the people that are closest to the problem, these types of systems offer additional benefits to organizations. One key benefit is the ability for IT and data analysts to stop being report developers and begin to deliver valuable analysis to the organization.

I know many organizations today that still approach data and data analysis with the old ‘gatekeeper’ mentality. They still want their IT staff and data analysts to be involved with all aspects of data. They don’t quite understand the value of interactive data in the hands of non-technical staff.

If you want to succeed with big data, you have to treat it differently than the data warehouse was treated. You need to think about opening up your data to allow easy, interactive access to every department within the organization. Of course, you also need to be able to secure your data but with the proper systems in place, you can ensure data governance and data quality while providing access for data analysis throughout the organization.

 This post is brought to you by SAS.

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