What do you put in your Data Analytics Toolbox?

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By Ron Maddox, V3iT Analytics

                                                            January 21, 2019

Many years ago, when personal computing was in the early stages, I remember seeing an Apple commercial. Too long ago to remember precisely, but it went something like this;

First gentleman standing gazing through an observation window at people using their PC’s. A second gentleman approaches and asks, “What are you doing?”. To which the first gentleman responds, “Trying to figure out what is the most powerful computer.” The second gentleman rejoins with, “That’s easy. It’s the one with the fastest processing power.” The first gentleman counters with, “I’m not so sure. I think it is one they use.”

I have always thought this to be one of the most powerful TV ads I have ever seen and it always comes to mind when I am asked to recommend an analytics delivery tool. My recommendation is always the one they will use. I’m generally met with rather dubious looks on this one, I have to say. I’m not trying to be glib, though. I really do believe in my recommendation. Of course, this always leads to the question, “Which one is that?” In my estimation, there is only one logical answer to this question, “Don’t ask me, ask them.” Then I deliver a quiet warning – there is probably not just one.

My experience has been that rarely does one analytics tool meet the needs of an entire organization. Even in small organizations information needs vary and how each individual prefers to consume information can vary from one task to the next. To expect one tool to be the one everyone (happily) uses is just unrealistic and counterproductive. A phrase I hear repeated often is, “We want to be a Data Centric organization”. I personally believe this to be an admirable goal that can lead to the accomplishment of any number of organizational goals. To be Data Centric, though, all decisions require supporting data before gaining approval. This will require a very robust data analytics capability, with broad participation from members across the organization overcoming both business and technical challenges. Putting the analytics tool, they use in their hands will go a long way towards cementing that participation.

To meet the changing needs for analysis of an ever-widening scope of data by an increasingly evolving diversity among how users consume information we must abandon the idea that these needs can be met with a single tool. Some people want to see numbers, some want visualizations, while others can’t possibly do their job without Excel. It can be split even further by those needing formatted reports, those that need to be able to slice and dice the data, some that just need dashboards and then those that just need access to the data and just stay out of the way. Trust me, if we only have access to one tool, somebody is not getting what they need.

The two main arguments I hear for having multiple tools is 1. The cost and 2. The skills and resources to support multiple tools. These two issues must be approached in the same manner as all investments – is the return I get for the investment greater than the cost. If data is truly one of our most important assets and the skills and creativity of the people analyzing that data are driving progress, then it is hard to see how giving them the tool they use will not result in positive outcomes. Without doubt, there will be added complexity to the technical landscape, increased requirements for management and governance of data and a greater need for both analytic and technical support skills. Each having the potential to result in higher costs. After thorough evaluation of the cost/benefit, if your decision is it is desirable to move forward and become a Data Centric organization, be observant, listen to the voices of the users and provide the tool(s) they use. Start small by targeting organizational areas with both a strong need and a strong desire for analyzing data. Pick something small enough to finish in a timeframe that will preclude Stakeholders tiring on waiting an outcome, but impactive enough to get attention. Collect and organize your dataset and then provide the data analyst multiple ways to access the data. They will not be shy telling you what they like or don’t like. Not only will you see what tools or types of tools they use, but through these small pilots you can begin to develop your data strategy and data governance models.

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V3iT’s mission is to deliver IT Services with a quick Value, clear Vision and at a high Velocity.   We leverage our technology talent, experience and portfolio of tools with the use of design principles to achieve the sweet spot at the intersection of what is technically feasible, viable from a business perspective and desirable from a user perspective.   This holistic approach creates your data journey roadmap with a focus on the desired informational outcomes and a platform that is constructed in a sustainable, scalable fashion.  The end goal is to ensure that what you get out of your analytics provides meaningful, accurate insights across your enterprise.

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