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The Truth Finds A Way

One trend that continues to gain momentum in the BI world is self service business intelligence, and it has IT groups concerned that the whole focus of a BI team is to champion a single version of the truth. MicroStrategy just released it’s desktop application for free, and version 10.6 is now available. If you have not taken a look at it, it is worth spending some time on. Tableau has built virtually it’s entire business model on self service BI. Any department that can’t get enough resources from the BI team can go and build their own dashboards now. Qlik is the same way. Now Microsoft’s Power BI has stepped into the ring with a growing offering. Alteryx, Sisense, Birst, Zoho – all of these are pouring resources into self service BI. IT groups are running scared, and maybe rightly so. Self service BI doesn’t have to have any training, any experience, any skill sets, any data governance, any single vision of what the single version of the truth is supposed to look like. Power to the people. Democratizing data like never before. Gartner is even saying that this is going to be the death of BI.

ms-excel

Or is it? People have always gone outside of the BI or the IT teams to build reports and analysis. It’s called Excel, or Access, and its been around for, oh I don’t know, a few decades? I’ve seen entire departments run from Excel and Access applications. You can’t stop them from using these. I’ve seen desktop computers that used to belong to an enterprising employee 10 years ago, that built an Access application that became mission critical to a department, and the department has seen the employees turnover two or three times in that period. Nobody remembers who the original developers were, or even what it was running, but each newly appointed department head got the instructions to make sure that desktop computer remained powered on under their desk and hooked up to the network. God help them is this computer dies or something. And these scenarios are a nightmare for IT groups that get handed to them to support – but you cannot stop it. Much like that Jeff Goldblum line from Jurassic Park – Life finds a way.

 

jp93-eggs1These new tools just give the enterprising users a new means to create things that BI teams or IT groups are going to have to support. They are given tasks to run the business, and then the BI group doesn’t have the time or means to provide them the reports or analysis they need to meet those new milestones that leadership keeps placing on them. And, nobody likes a whiner, so they invent what they need outside of the process. Business is happy. Users are happy. IT is blissfully unaware. All they know is that they stopped emailing them asking for a status on their request and didn’t even miss the emails. Is this really such a bad thing? I mean, if the BI team built every single thing the business thought it needs to run then they would collapse under their own weight. Rather than cringing at these outlaw scenarios, if you look at them as a proof of concept exercise, and let the POCs that live life past a year or some determined amount of time that proves the reasoning and the needs were real, then really everyone who does these are helping out the BI team.

 

Rather than seeing these activities as competition or amorphous growth that cannot be supported, BI teams should looking to guiding these rogues in a way that helps keep some sanity to possibly taking over the project when it has matured. Choosing one self service BI tool and embracing it, training on it, training others on it, would be a much better alternative than leaving it up to the department and needing expertise on 5 or 6 different tools de jour. For one, it enables you to hire or train a resource for the BI team to assist users in developing their own projects and for taking over projects that have grown to big to be a department only project. Secondly, it provides some consistency to the rogue POCs so that the company looks like it knows what it is doing. Third, taking the lead to facilitate this movement means BI and IT can guide the company down the path to some degree, rather than being handed who knows what to support. Don’t fight the tidal wave. Grab it, embrace it, lead it. Sticking your head in the sand is never a good strategy.

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Mobile Development vs MicroStrategy Mobile

Mobile-Application-Development

I had a potential customer ask me yesterday if we could build mobile apps. Apparently they had just spent a lot of money on an app that would allow them to collect data in the field, but it did not integrate with any of their shipment data or POS sales data to complete the picture for their field personnel. This company also did not have the resources to build any kind of custom app from scratch themselves. So, if you are thinking about taking this feat on, let me break it down for you in a few high level steps.

There are many scenarios that you can walk down, but I am going to walk down two specifically: Custom app vs. MicroStrategy mobile app.

Scenario 1 – Building a custom app from scratch.

First off, you are going to need a good overview on iOS development. Try here for starters. When you go down this road, you are going to need a Mac to do your development on. You will also need a developer account with Apple to be able to publish the app. If you want to be backwards compatible, you may need more than one Mac to test on, as the XCode environment is tied to the OS (from what I can tell). You also will need an iPad or two, or three for testing. If you want to support iPhones, you will need some of those. What about the version of iOS? We are currently on 9.x. Do you want to support 8.x as well? While there are testers for some of this in xCode, if you want to make sure your app works across all of these environments I think it is a good idea to develop a test plan on actual HW so that your app isn’t flakey.

On your app side, you are going to be writing a lot of Objective C code to run the app, but you are also going to need a service in the background to dish out data and be the backend for the app. I doubt you would want the app to connect directly to your database. This service should also handle secure logins, passwords, user management, resetting a user password – all of the plumbing that will enable a user to mange the app, their account, and themselves. It also needs to grab data from the data warehouse and package it back to the app. You might need to compress it to make the app more faster.

Now, once you’ve climbed through all of that, you get to manage change management coming from user feature requests, from corporate, from bugs. You get to roll out new versions, craft a test plan to make sure it all remains backwards compatible with older versions of iOS, across all apple devices. To keep up, you may have to juggle a roadmap with multiple versions in play at various lifecycle stages – or in other words, you may be performing user acceptance testing on version 2.5 while you are working on publishing version 2.4 to the app store, as well as scoping changes to version 3.0 to be released next quarter.

I would not say any of this is rocket science, but it can grow to be quite an undertaking if you want to do it right. Wait – where is your Andriod app at? Corporate CFO has an android and wants his version for his phone. Where do you start for that? Now, remember that app that you thrashed in the comments because it was so buggy last week? Feeling even the least bit sorry for that company if this is one or two people trying to keep up with all of this?

Scenario 2 – MicroStrategy Mobile

Now that your head is spinning from trying to develop and support a custom app, there is a bright side to all of this – MicroStrategy Mobile. There are lots of other platforms, and this article could go on for days, but we have direct experience in MicroStrategy Mobile so we will give a glimpse of this one to compare and contrast.

First off – you will need a MicroStrategy environment. This of course is not free – you will need to get an enterprise license for this and each user will need a license. Second – you will need to develop your data objects. This also is not for the faint of heart. Most companies do all of this because they want slick reports, dashboards, and gorgeous data visualizations., regardless of mobile or not. This is pretty much MicroStrategy’s bread and butter. It handles all of the service back end, scheduling, report automation, security, throttling, and presentation. You just need to get your data into a data warehouse. There are lots of strategies for BI – but, if you go down the MicroStrategy route, then you inherit a Mobile strategy second to none.

All of the reports you built for your monday morning dashboard can translate directly into a mobile app with just a small amount of effort. There is no source code you need to master. MicroStrategy can handle much of the iOS compatibility and hardware testing. It’s almost like a buy one, get one free. You get enterprise class reporting along with enterprise class mobile.

MicroStrategy also has transaction services, which allows you to input data on the iPad. Need to capture store shelf quantity, or survey questions? No problem. It can capture data alongside all of your enterprise data warehouse metrics for a complete, 360 degree dashboard. It can show images, take pictures, capture data, report data, drill into your data, visualize your data in graphs and charts. You can build an entire customer service app – just in MicroStrategy – with your company icon and logo.

Summary

Now, if you just needed a mobile app, is this the easier route? Depends on how you look at it. There is probably equal amount of effort getting both scenarios up to speed. I won’t lie and say that MicroStrategy is easy. The payoff comes downstream when you need to support your app. If someone requests changes to your app, you can make a change to your MicroStrategy dashboard inside of MicroStrategy – without needing to recompile, test, and publish your app to the Apple app store. This change, depending on the significance, could literally take you 2 minutes to log in and change something minor. Want to roll out a version of this app for a new customer? Copy, paste, and change the logo – again, maybe a 10 minute change. Because of the object oriented development nature of MicroStrategy, each dashboard will inherit all of the building blocks in the foundation you build. So if you formatted a date wrong, you go change the date attribute. All of your reports, dashboards, and mobile apps then inherit the change – no need to touch them.

Hours or days – not weeks or months. No objective C code to maintain. No API service backend to maintain.

80% of what you build in MicroStrategy is reusable. This is not the case with Tableau, Qlikview, SSRS, Crystal Reports, or custom ASP.NET portals. This is why we lead with a MicroStrategy solution. If we build a customer a neat dashboard to be consumed in a web browser, and the CFO determines they want it on their iPad, we just have to copy, paste, and then do a little resizing so it fits nicely and viola – instant mobile app. Maybe less than a day’s work. If you are building a custom app from scratch – where is your git repository hosted at again?

If your organization could benefit from a BI platform to deliver reporting,dashboards, and data discovery – and also needs a mobile app strategy – then this seems like a no brainer to me. Even if you think it might be useful down the road, then having a combined strategy for BI and mobile makes sense. If you go down the road of separate BI and mobile, then you are eventually going to have to join them up, and it will be twice the support at that point. Twice the cost and twice the fun.

Please contact us today to see how we can help you with your mobile app and BI challenges.

What is Cluster Analysis? And Why Use It?

2015-09-14 15_01_17-K-Means Clustering - Store. MicroStrategy 9

Why would you want to use cluster analysis on your retail sales data? Well, cluster analysis helps you identify non-independence in your data. Here is an example to help illustrate the point. Lets say we want to ask loads of teachers from many different schools what they think of their principal. If you ask two different teachers from two different schools, you will get two completely different answers that will be independent. But, if you ask two teachers from the same school, the answers will not be completely independent and could be very similar – but not EXACTLY the same.  Now if your job was to take the raw data and try to predict which school each teacher came from based on their answer – then you have an application of clustering.

2015-09-15 09_53_10-K-Means Clustering - Store - Original. MicroStrategy 9

The same thing can be applied to Walmart store performance for a supplier. You have some data points for a store like how long that store has been open, how many competitors it has located in its vicinity, what was your products sales performance for that store, some demographics for that area like unemployment and population, possibly even some historic weather data. Now you use a clustering algorithm to group your stores that are most closely related. This could be the first step in identifying under performing stores and why. It could give you a viable store list for a product test based on more than sales performance. It might help you further identify your product identity and who your actual customers are using enough demographic data. You might not find anything you didn’t already know. The important thing is that you are diving into your data to truly understand it on a level you never have before, and uncovering one of these nuggets could be millions of dollars difference to your company.

Once you’ve built your base analysis, and in our case we built our report that you see above, turned it into an in-memory cube, and then built a MicroStrategy dashboard on top of it – we can then explore slicing and dicing our data along the different data points to help identify if any of the metrics in our analysis are a key contributor to a cluster alignment. This way we can determine what factor affects sales the most. Could it be store age? or store square footage? or unemployment? Ethnic breakdown? What of these are driving markdowns?

The great thing about using this analysis as a MicroStrategy dashboard is that it is pretty easy to tweak to look for your top performing stores, and refreshing the data source is very easy. In fact, this report could be automated each week and emailed to you. There might even be an application to look for cluster changes and have something like that generate an alert so you only need to be bothered if anything changes.

Contact us today to discover how Vortisieze analytics can help you explore your own data science.

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Exploring #BigData Business Models & The Winning Value Propositions Behind Them | #CPGMarketing

This article, by Justin Lokitz – a thought leader in big data, provides an excellent overview of three distinct business models using big data.  Any one of which, or a hybrid, can be incorporated in a CPG category manager’s analytics process.  The article is worth a separate read but the main points are summarized, and applied to CPG, below:

It goes without saying, innovative, sustainable Big Data Business Models are as pervasive and sought after as they are elusive (i.e.  “data is the new oil”).  For every startup that designs and implements what amounts to a devilishly simple and effective big data business model (see any social network), perhaps changing the entire landscape with it, there are literally hundreds (if not thousands) of larger, more mature companies looking for ways to monetize their own big data in the hope that they can capture new revenue streams (and compete effectively in the future).  Of course some of the larger, mature companies have done quite well in this regard.  Apple (40 years old) and Amazon (20 years old), for instance, have vastly different business models.  Yet, both companies have built solid business models around big data; both use big data to present to consumers products and services that might be relevant to them.  Similarly, Netflix and Pandora, 18 and 15 years old respectively, designed brand new big data business models around understanding and creating value for customers in ways that seemed like magic at the time.  So, what’s behind these business models?  And, are there other business models that might help other (mature) companies create, deliver, and capture value using big data at the core?  The answer (to both questions) is simple: it’s all in the value proposition.

He further states in his introduction:

“Fall in Love with the Problem, Not the Solution.” As simple as this quote is it speaks volumes when considering how mature companies tend to think about utilizing their own big data stores to create new business models.  That is to say most mature companies first ask, “What big data do we have today?” followed by, “how might we sell this data?” Looking back on my favorite aforementioned quote, you can probably see the discrepancy here: most mature companies believe there is some mythical marketplace where they can simultaneously sell their big data whilst not pissing off their customers.  These assumptions are more often than not wrong.  Moreover, while there are LOTS of “problems” to fall in love with when it comes to big data business models, in order to provide some focus, this post highlights three categories of big data business models based on their value propositions and customers (e.g.  DaaS, IaaS, and AaaS respectively).

Big-Data-Pyramid

  • Data as a Service (DaaS)

DaaS hinges on a value proposition for supplying large amounts of processed data with the idea that the customer’s job-to-be-done is to find answers or develop solutions for their customers.

For CPG companies partnering with large retailers as a trusted supplier – this usually begins with the POS/Inventory data supplied at the vendor level or, where appropriate, the category level.

The granularity of data can be daily or weekly and provide historical data – usually 104 weeks.  While the author speaks in general terms about marketing data to monetize it (in fact the entire article has an eye toward this), CPG companies cannot sell retailer supplied data.  This does not mean that you, as a CPG category or sales manager cannot monetize the data.  For you – monetization occurs when you use analytics to gain insights to share with your buyer(s).  The goal of this activity, of course, is to flank your competitors within the category, increasing your brand’s market share within the retailer ecosystem.

Part of the Vortisieze service offering is providing a fast, clean, single source of the truth, aggregated data and the analytics tools to empower you to produce your own insights.

data-as-a-service

  • Information as a Service (IaaS)

IaaS focuses on providing insights based on the analysis of processed data.  In this case the customer’s job-to-be-done is more about coming up with their own conclusions or even “selling” an idea based on certain information.  Additionally, IaaS customers don’t want to or do not have the resources to process and analyze data.  Rather they are willing to exchange value for analysis from trusted parties.  Unlike the DaaS business model, which is about aggregation and dissemination of lots of processed data for customers to create their own value propositions from, the IaaS business model is all about turning data into information for customers who need something – and are willing to pay for something – more tailored.

Because we have category manager DNA in our company’s DNA, Vortisieze can meet this need by providing ready-to-use analytics, dashboards such as Business at a Glance (BaaG) for example.

information-as-a-service

  • Answers as a Service (AaaS)

AaaS is focused on providing higher-level answers to specific questions rather than simply the information that can be used to come up with an answer.  CPG companies who implement the AaaS business model do so in gain answers to answer specific questions.

This business model, as you might guess, is the top of the pyramid when it comes big data.  The key with this business model is that given the CPG company’s ability to create real, trusted value in the answers it provides to buyers, buyers take note and value the insightful answers provided.

When a category manager partners with Vortisieze by asking very specific questions needing answers (remember strategy drives questions), we can provide answers to your most important questions.

answers-as-a-service

 

Vortisieze technology, unlike rigid DSRs or yesteryear, provides pliable, and rapid, solutions to meet your analytics needs.

Contact us today to discover how.

 

About the article author:

Justin Lokitz is Strategy Designer & Managing Director at Business Models Inc.  San Francisco

Source:  Exploring Big Data Business Models & The Winning Value Propositions Behind Them

 

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