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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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Get A Data Scientist to Work On Your Problem For Free

According to the Consumer Goods Technology and RIS 2016 Analytics Study, 33% of companies lag behind their competitors in analytics skills and people, and 31% lag behind in analytics tools.
2016-05-17 10_27_33-2016 Retail and Consumer Goods Analytics Study.pdf - Adobe Reader

In an effort to help, we are seeking CG companies that have a real data science need or question that they would like to see solved or automated, and we would like to help for free. Whats the catch? Well, we have a short survey we want to collect data on and use to analyze the industry, specifically which industries are having the most problems, but we also want to examine the real world problems out there and see if we can help solve them. We are not collecting any personally identifiable information to sell off to anyone – we just want to chew on some data science problems with you and see if there things we can do to help. With 77% of company respondents to the Consumer Goods Technology and RIS 2016 Analytics Study stating they either planned to or did not have any investment in data science, here is a way to possibly test drive a data science team at no cost to you.

Just fill out the 18 question survey below and if you have a real question and think we can get the data to solve it – then you are in! We are not limiting the winning questions so more than one question could be selected.

2016-05-17 10_41_56-Retail Questions Needing Answers

CPG Retail Data Question Survey

If you have any questions about the survey or want to find out what we do, feel free to contact us here.

 

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NWA BI Meetup – Thursday, April 21

Hey NWA BI Data Ninjas!

We’ve got a place, a date and time for our next meetup. Thursday, April 21st at 5:30 PM – at the Mars offices thanks to Chris.

We have not locked in an agenda yet, so if you would like to present a project you are working on or have something you would like to see let me know.

Also, you may have noticed that we have changed the user group name. 75% of the survey respondents preferred “NWA Business Intelligence User Group” as opposed to the previous “Arkansas Area MicroStrategy User Group”. I’m sure we will still talk quite a bit about MicroStrategy, but this opens us up to other tools more easily.

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My Analytics Budget is $0, So Now What?

The reality is, that some companies just don’t have a big enough presence in Walmart to warrant any kind of real IT spend. It was a huge deal when they brought on their first full time analyst that has some experience, and is located in Bentonville so that they can meet with their buyers whenever they need to. You get your company issued laptop, with a fresh install of Microsoft Office, a retaillink ID, and you are off and running, right?

FundingPlanPRONo Problem – you are an excel wizard I bet. But as you are constantly maintaining horrific formula pages and trying not to break everything when your boss is requesting new feature engineering in their 20 page workbook, have you ever wondered, there has to be a better way?

You get what real data integration brings. Process automation that can refresh data without inventing the dashboard each and every single week. Feature engineering without such massive headaches. Adding new data sets to a model in a database, not a new tab. Oh the things you could do if you could get that time back.

Something that came about in MicroStrategy 10 was a new feature called Data Wrangling. This allowed an analyst to combine corporate data from the data warehouse with adhoc data and gave you come cleansing and harmonizing functionality. You’ve seen this need before. You get a data set where some states are all spelled out, while others have the two letter code. You see two rows for Texas (Texas and TX), and you have to scrub this in excel before it is usable. Or your data warehouse team does this in their ETL. Well, now you can do this directly in MicroStrategy with data you import yourself. You only need the $600 copy of MicroStrategy Desktop. Build a recipe and save it, and now this is semi-automated when you need to refresh your data. All you need to do is kick it off, and all of your cleansing tasks have been saved and are rerun.

I’ve always thought this was cool, ever since they showed this off at MicroStrategy world last year. But back to your budget of $0. Even $600 is going to be tough to get permission for. Well, I took a tour through a brand new product today that looks like it can do many of the same data wrangling techniques as MicroStrategy Desktop, but the cost is FREE. $0. Nada. It’s called Talend Data Preparation. It has a free version and a subscription version if you would like to work in a big environment and integrate with their other ETL platforms, but the free version looks like it is perfect for the lone rangers out there munging spreadsheets and cleaning data each week just so they can get to their analysis.

Check it out here: https://www.talend.com/products/data-preparation

You still need to kick it off when it’s time to refresh your data, but it lets you build recipes and save them, automating much of your work to refresh your data. It looks like it can connect to HTTP, local, and HDFS data sets.

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Is there ever a perfect storm for suppliers?

walmart-snow

In the article below, RetailWire talks with Weather Expert Paul Walsh on customer behavior, and what retailers are doing to balance things out.

“What almost always happens when you get a big event like this is you really see three phases from a retailer perspective,” Walsh told Retail Dive. “Actually, it’s really from a consumer perspective, and the retailers’ job is to be ready for their customers’ needs.”

Retailers don’t lose or gain sales as weather events hit, unless their supply chain is not prepared for the push ahead of the event. What this signals is that retailers are getting out ahead of these events using weather data, and suppliers are being increasingly asked to help anticipate supply chain strains ahead of the curve as well.

“The weather ate my homework” is no longer going to be a viable excuse in the coming months and years. There will be an expectation that a supplier network will need to be out ahead of this. It won’t matter if you are a top tier supplier maximizing your category, a mid-tier supplier scratching and clawing for their business every day, or a small supplier just trying to keep up. The forecasting models are becoming more and more accurate. Not having your products attributed to weather sensitivity will be a hindrance.

oos-walmart-snowstormIt’s also important to consider “just weather data” may not be enough. Feature engineering both the weather data to tailor it to your products and your products attributes may be required to extract enough insights as to what weather patterns and events are effecting your sales. Make sure you have people on board that can do this with your data, and it may take some experimentation, since no two product assortments are the same. Having the data at the same level as your geography dimension also helps take some of the burden off of your analytics platform. Its a lot of data, and most of it comes at the weather station level.

Have I mentioned yet that we can do this for you? We can provide weather data at the zip code level, and we have experts on staff that can help with your feature engineering, as well as your reporting and data mining.

You can read the whole article here

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

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Northwest Arkansas Meetup for January 1-28-2015

meetup_logo_1

The NWA Area MicroStrategy user group is kicking off 2016 with a new meetup group. Their first meeting is scheduled for Thursday, Jan 18, 2016 at 6 PM. The location is TBD and will be announced shortly. If you haven’t joined or RSVP’d yet head over to Meetup.com and RSVP now!

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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.

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Is A Data Tidal Wave Heading Your Way? #CPGBI #BigData

Consumer Goods Technology came out with a whitepaper today on Bridging the Data Divide. In this whitepaper is a quote from Gordon Wade, senior vice president of category management best practices at the Category Management Association (CMA):

“Every category manager, whether at a retailer or a manufacturer, has more data than anyone could possibly review, much less analyze and understand,”

The paper also goes on to discuss some very neat things people are doing with mobile and shopping data to simulate store sales and people movements through aisle changes and shopper personalization. This might be the beginning of the tidal wave that is coming. My question to you is – what is your data strategy? Are you feeling like you are already drowning in data? The goal is not to drown retailers or suppliers, but to find ways to integrate data that will keep your business floating in the short and long term future.

data-explosion2

It is clear that the ability to combine new data sources in innovative, cohesive ways will be integral to grocery and CPG success. We can help with that. Store sales and inventory, weather, demographics, store traits, social media, supply chain – we combine all of this into powerful, user driven analytics in a drag-n-drop, build your own reporting and dashboard environment. We are also willing to take in your specific data sources to give you a complete picture of your business, and apply statistical models for predictive metrics to your data for even more insights.

Please contact us today to see how we can help you out of your data deluge.

Source: CGT

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The Crystal Ball – Exploring a Walmart POS Seasonal Forecast #CPGBI

One of the most common uses of machine learning in analytics is to forecast time based data. It’s the quintessential sales question – what will my sales look like next month, or next quarter, or next year even – the proverbial crystal ball, if only it were that simple. Something that we were fairly quickly put together using MicroStrategy’s visual insights and R-Integration is an “Ordinary Least Squares” regression algorithm to fit the best curve that captures the general trend and seasonal variability of Walmart POS data to predict future sales.

The formula is:

Y = bTrend*Trend + Σ (bSeason_i*Seasoni) + bIntercept

where

  • Y is a numeric metric (called the Dependent Variable)
  • Trend is a numeric metric that’s an arithmetic sequence of monotonically increasing values
  • Seasoni is a binary indicator metric derived from Season, a numeric or string metric that represents each season. Binary indicators have a value of 1 for the i-th season and are 0 for all other seasons. For n seasons, there are n-1 XSeason_i variables
  • bTrend, bSeason_i, and bIntercept are coefficients determined by the regression algorithm.

2015-09-28 09_32_23-WM POS Seasonal Monthly Forecast. MicroStrategy 9

As sales drop in for the coming months, we should be able to gauge the accuracy of our prediction for the rest of the year. If this hold true, we could use it for some of our business decisions going forward. We could also look at just the latest complete months, so we would not see that monthly drop in month 201402. We could also look at this weekly by switching out just a couple of metrics.

Something else we could do is create a variance against actual POS sales, and if the variance exceeds some number, like 10% difference plus or minus, we could create an alert and send out warning emails to key people in our business so that they can plan for unanticipated high sales, or research a drop in sales.

Please contact us to see how we can help you leverage regression analysis with your data to help predict your future!

Business Intelligence vs Analytics vs Big Data vs Data Mining #CPGBI

The business intelligence landscape is rapidly changing, and there is a lot of confusion on what the difference between BI, Analytics, Big Data, and Data Mining is. Whats more, you turn your head for just a minute and then there are whole new classes of terms that you’ve never even heard of before.

In the below article from Dennis Junk at Aptera’s blog, he breaks it down into four main categories to help you understand. As a CPG company supporting Walmart, I believe it is important to have a strategy for all of these concepts – especially in the wake of their new supplier terms and squeezing they are employing. If you don’t, we can help you with that, as we are a full service Business Intelligence company that can deliver Analytics from Big Data sources and use the R statistical package to mine the data for meaningful insights.

Business Intelligence:

This is the broadest category and encompasses the other three terms here (at least as they’re used in a business IT context). BI is data-driven decision-making. It includes the generation, aggregation, analysis, and visualization of data to inform and facilitate business management and strategizing. All the other terms refer to some aspect of how information is gathered or crunched, while BI goes beyond the data to include what business leaders actually do with the insights they glean from it. BI therefore is not strictly technological; it involves the processes and procedures that support data collection, sharing, and reporting, all in the service of making better decisions. One of the trends in recent years has been away from systems that rely on IT staff to provide reports and graphs for decision-makers toward what’s called self-service BI—tools that allow business users to generate their own reports and visualizations to share with colleagues and help everyone choose what course to take.

Analytics:

This is all the ways you can break down the data, assess trends over time, and compare one sector or measurement to another. It can also include the various ways the data is visualized to make the trends and relationships intuitive at a glance. If BI is about making decisions, analytics is about asking questions: How did sales for the new model compare to sales for the old one last month? How did one salesperson do compared to another? Are certain products selling better in certain locations? You can even ask questions about the future with systems that perform Predictive Analytics. Some companies treat analytics and BI as synonymous—or simply rely on one to the exclusion of the other. But analytics is generally the data crunching, question-answering phase leading up to the decision-making phase in the overall Business Intelligence process.

Big Data:

This is the technology that stores and processes data from sources both internal and external to your company. Big Data usually refers to the immense volumes of data available online and in the cloud, which requires ever more computing power to gather and analyze. Because the sources are so diverse, the data is often completely raw and unstructured. Since you’ll probably be using this data for purposes it wasn’t originally intended to serve, you’ll have to clean it up a bit before you can garner any useful insights from it. The systems you put in place internally to track KPIs are obviously the main source you turn to when you need to answer a question about your business, but Big Data makes available almost limitless amounts of information you can sift through for insights related to your industry, your business, your prospective customers. Big Data is the library you visit when the information to answer your questions isn’t readily at hand. And like a real library it allows you to look for answers to questions you didn’t even know you had.

Data Mining:

Finding answers you didn’t know you were looking for beforehand is what Data Mining is all about. With so much information available, you can never be sure you’re not overlooking some key fact pointing the way to better performance. Data Mining is the practice of sifting through all the evidence in search of previously unrecognized patterns. Some companies are even hiring Data Scientists, experts in statistics and computer science who know all the tricks for finding the signals hidden in the noise. Data Mining probably fits within the category of analytics, but most analytics is based on data from systems set up to track known KPIs—so it’s usually more measuring than mining.

Not everyone will agree on these terms, as Dennis points out in his article, but it’s a good start. As a core strategy I believe your BI should encompass all three: easy to use analytics that allows your users to ask their own questions, big data to capture MORE than just sales data, and data mining so that you can leverage all of your data for the best insights possible.

Please contact us to see how we can help you create a strategy in all of these areas that might unlock a competitive advantage you didn’t know existed!

Source: http://blog.apterainc.com/