Turning Big Data From A Liability To An Asset – Point 2 Taking An Enterprise Wide Approach

Getting value from Big Data is a headline that is constantly being offered daily in multiple publications. A lot of what is said about Big Data is really just a spin on ways to sell “re-wrapped” products and services. My hope is that the information that is being offered in this blog provides meaningful suggestions that allow your company to gain significant competitive advantage from Big Data.

Companies are aggressively trying to figure out what Big Data means and how they can tackle the multiple obstacles they anticipate in order to gain significant value. This posting is the second in a series focused on the problem of addressing data liability. The goal of this series is to demystify the whole notion of harnessing Big Data from being a seemingly impossible, daunting task to an opportunity to create an invaluable asset that drives significant financial performance improvements. In the last issue, we talked about building organizational consensus. In this issue, we will look at the importance of building on that consensus to support an enterprise wide approach to maximize the value of Big Data.

You might find the following article of interest. It also addresses the need for an enterprise-wide approach to Big Data: click here

I am currently reading the book Deep and Wide by Andy Stanley. Although the topic is on a completely different subject, the title of the book provides synergy to taking an enterprise wide approach with Big Data. Let’s explore this further.

To tackle the point of gaining cross-functional buy-in to your Big Data approach, you need to give everyone at the party something they want. But how can you accomplish this to satisfy the specific Big Data needs for Supply Chain, Sales, Marketing, Operations and Finance? Doesn’t this only increase the time and complexity associated with the effort and push it one step closer to inevitable cancelation?

The answer is no. Effective solutions do not approach Big Data from a “functional silo” point of view but from an “end to end supply chain” perspective in order that the transactional data can be repurposed to serve the multiple needs of the organization. Taking a holistic approach that includes suppliers, manufacturing, storage, transportation, inventory and product returns provides an end to end level of scope that can then be used to serve multiple functional needs. This is the Wide piece of the puzzle having one source of trusted information and is a key criteria to building effective Integrated Business Planning (IBP)solutions using Big Data.

But what about the Deep side of the solution. To be meaningful, Big Data solutions have to provide for meaningful insights that drive better organizational decisions. This requires the ability to get to very specific performance information, information that provides insights and is actionable. You might be thinking; what, detailed information about end to end operational performance accessible to multiple organizational users?You bet! The cloud now provides the processing capability to take the first step to harness Big Data that drives value by increasing financial performance and competitive advantage.

I am often in meetings with a group that was not the original sponsor of the company’s Big Data initiative. We will be reviewing IBP information focused on a specific operating strategy. The conversation will go something like this:

“Yes, we think that’s the case, nothing new there. But wait, look at those details! Can that be right? How did you determine that? Can you drill into that further?

I wish we had known that specific information on that (customer, product, channel – you pick the area) yesterday.”

Avoiding approaches that use silos of Big Data is a huge step in gaining high impact results. Making very specific operation details available in ways that are meaningful to each organization eliminates conflicting analysis and confusion on operating performance. Going Deep and Wide using an Enterprise Approach is key.

In fact, this goes back to getting everyone to buy in. Give everyone something to make their job easier, something to make them smarter and something that makes them more efficient and you will have turned data into an asset instead of it being a liability...

We would appreciate hearing your thoughts and comments. All the best, Richard

Turning Big Data From A Liability To An Asset - Point 1 Organizational Consensus

In my last blog on Big Data we discussed how Big Data can support 4 distinct forms of decision making: Descriptive, Prescriptive, Predictive and Cognitive Analytics. However, in order for any analytical solutions to be meaningful, the issue of data liability needs to be addressed.

Starting in this posting and in the next three (3) releases for this blog, I am going to offer a series of points, which help solve this data liability issue. The goal is to demystify the whole notion of harnessing Big Data from being a seemingly impossible, daunting task to one of an opportunity to create an invaluable asset that drives significant financial performance improvements. Naturally, there are a whole host of actions required to fully harness Big Data but in this series we will focus on just four: building organizational consensus, taking an enterprise wide approach, placing priority on data governance and finally creating repeatable and measurable impact.

While I was the President of CAPS Logistics for over 8 years, the company serviced over 16% of the Fortune 500 in various forms of supply chain decision support applications. These efforts spanned the globe from supporting the expansion efforts of a worldwide soft drink company, to the redesign of supply chain networks for multiple CPG and specialty manufacturing companies in addition to providing different transportation solutions to one of the largest companies in the waste management industry. The technology was proven, the people were bright and the focus was to provide the best solutions possible. Unfortunately, in certain cases, the implementation of these carefully engineered solutions was either slowed down or even put on hold. Why? Other departments would offer objections often citing concerns about the “quality” of data used for the analysis. Typically, the nail in the coffin would be that if they would offer that their data concerns were correct, the integrity of the solution could cause the company to miss its revenue targets. Sound familiar? The end result was that the company did not attain the competitive advantage that was possible.

Let’s take this lesson to the world we live in today, a world of exponentially growing data associated with the operation of your enterprise. The problem sited above had two issues. The “quality” concern which will be addressed in a future posting on data governance. The second issue was not having cross-functional consensus. In the projects mentioned above, efforts were made to involve other departments at every stage of the project but gaining supply chain efficiencies were not their highest priority. Therefore, these other functional groups had no real buy-in in the work effort.

If you believe that Big Data has the opportunity to drive significantly recurring financial improvements, then the table stakes are even higher with regard to early organizational buy-in. Buy-in with regard to getting everyone on the same page on how to repurpose and use Big Data to empower multiple forms of new analytical and strategy development capabilities. I am guessing that many of you are saying “yea, right for our company; this would be comparable to building Noah’s Ark.” You may be right but it is a challenge that deserves careful consideration as offered by the following quote by Benjamin Franklin:

“By failing to prepare, you are preparing to fail.”

Success will require having the right level of Executive sponsorship and taking advantage of the power of cloud technologies and proven methodologies. In addition, other key points need to be integrated into your approach including obtaining cross functional consensus on any data issues. If this is not a mandate, you run the serious risk that organizational questions will surface which can stop the entire effort.

So why go to the effort? Isn’t the political risk too significant and the task too big to undertake now especially given all of the mission critical projects that are already established for the company? That might be the right answer but let’s look at it another way. Is it possible that your Board and certain members of your Executive Team are wondering if the company will be left behind when your competitors harness the value of Big Data? Value that is measured by increasing financial performance and competitive advantage. Only you know the answer to that question, but if the decision is made to take the first move advantage, be sure the process you use requires cross functional organizational consensus as a cornerstone of the solution.

Check out this video, which can help get your cross-functional team invested in Big Data: https://youtu.be/DCffaA-Cra4

We would appreciate hearing your thoughts and comments. All the best, Richard