Aloha Facebook, Where am I Today?

Facebook is set to fight fake news by using artificial intelligence. A good way to practice may be by playing a bit more around with their geolocation intelligence.

Today I, as far as I know, are on the Canary Islands. This is a part of Spain, though a little bit away from the motherland down the Atlantic Ocean off the North African coast. A main town on the islands is called Las Palmas.

However, according to Facebook I seem to be in a place called Las Palmas Subdivision on Hawaii in the Pacific Ocean on the other side of the globe with Hawaii being a bit away from where it were last time I looked on a map.

Facebook Geolocation Hickup

 

The Real Reason Why Your Business Needs a PIM Tool

Today’s guest blog post is the second one from Dan O’Connor, a United States based product data taxonomy guru. Here are Dan’s thoughts on why you should have a Product Information Management (PIM) tool:

Over the past year I have moved from a position of watching a Product Information Management tool, or PIM, being installed, to working for a PIM vendor, to working through the process of installing a PIM tool from the client side. In the same way that I justified buying a sports car to my wife based on the utilitarian value of having 350 horsepower at my disposal, I’ve seen many different justifications for installing a PIM tool. From “Micro Moments” to “collaborative data collection” and “syndication”, terms are tossed around that attempt to add to the value of a PIM installation.

The simple truth is there is only one reason you need a PIM tool. Every justification is solving a symptom of a data problem in a business, not the core problem. Every good management executive knowns that solving symptoms is a rabbit hole that can cost time and money at an incredible rate, so understanding what the core problem that requires a PIM in your business is vital to your business growth.

PIM messageControlling your Messaging

That core problem your business needs to solve is product messaging. Simply put, without a central hub for your data your business has a lack of control over how your product messaging is spread both internally and externally.  If you are still working in spread sheets or collecting data multiple times for a single product for different channels you have lost most of your product messaging structure.

PIM is a tool that solves that problem, and the symptomology that comes with it. Does your business spend too much time assembling data to meet downstream partner needs? You have a product messaging problem. Is your business’ ability to ingest data limited by spread sheets transferred over network folders or email? You have a product messaging problem.

All the benefits of PIM can be summed up into a simple statement: If you want to be in control of your product brand and your product data quality your business needs a PIM tool. Do you want to reduce product data setup costs? You need a central location for all your product messaging to do so. Does your business have product data quality issues that occur due to poor adherence to best practices? Poor data quality affects your product messaging, and can be solved by a PIM tool. Is your business spending too much time chasing down emails with product specs and spread sheets full of setup data? These bad workflow practices affect your ability to provide a consistent message downstream to your business partners, whether your business is B2B or B2C. They are a symptom of your poor product messaging control.

The True PIM ROI Story

The central premise of a PIM tool is to standardize and normalize your product data collection and setup workflows and processes. If your business looks at a PIM tool only for this metric your vision for PIM is limited. Syndication, the distribution of data to consuming internal and external systems, is another huge benefit to PIM. However, if the product messaging your PIM system is sending or receiving is not well controlled within your PIM your vision is incomplete. There is not a single benefit to PIM that you cannot add the terms “with a consistent approach to your product messaging” to the end of.

Why is product messaging so important? In previous blogs I have demonstrated how failures in product messaging lead to odd product experiences, especially when you look at the messaging across platforms. If your web store shows a length for a product and your channel partner shows a different length you have a product messaging problem. If that product data came from a central source that issue would not exist. It might be as simple as the downstream partner swapped length for depth and there isn’t a true data issue, but to your customers there is an inconsistent product data message.

Extrapolating this out to something as simple as web descriptions actually validates this business case. If you provide a basic web description for a product based on an individual manually typing in marketing copy into a web portal you have lost control of your product messaging. That same person may be responsible for typing that web description in 4 different places, and without a central repository for that data the chances that those 4 messages will complement each other is slim. Add to that the fact that many major retailers edit web descriptions to conform to their standards after your business has completed product setup and you are less in control of your product messaging than you imagined.

Having a PIM tool solves this. You have a single source for web descriptions that you know will be represented in a singular repeatable fashion downstream. You can map your dimension attributes to your downstream channel partner dimensions, ensuring that the appropriate data appears in each field. You can customize web descriptions in a controlled and normalized environment so that you have more control over how those descriptions are customized by your channel partners.

The Importance of Product Messaging

Product messaging is your voice to your customers. As B2B ecommerce follows the path blazed by B2C it has become more important to have a consistent and controlled message for your products to all your customers. Spread sheets are not capable of that task, and email is not a mechanism for maintaining product data quality. Automated systems with proper workflows and data quality checks are paramount to ensuring the voice you expect your customers to hear is your business’ voice.

Reducing catalog printing costs, syndication of product data to channel partners, and reducing product setup headcount are valid reasons to install a PIM tool. However, they all should be part of a greater goal to control your voice to your customers. Those benefits are symptoms of a need in your business to have a unifying voice, and not including product messaging control as the overriding goal of your PIM installation is a strategic error.

In having performed many PIM installations here is the impact of not seeing product messaging control as the overarching goal. A company I worked with went through the process of installing a PIM tool, and we reached the point of remediating their existing product data to fit the new model. This company, who had invested heavily in this project, decided they did not want to perform any data remediation. They simply added back into their PIM tool every attribute that had existed in their old system. There was vision to improve the data they were displaying to their customers: They simply wanted to speed up product setup.

That business has spent the last 6 months undoing the benefits on controlled product messaging. It was less costly to them in the short term to simply replicate their existing data issues in a new system. Their old product data was unwieldly, hyper-specific to channel, and involved writing product titles and web descriptions manually for each channel. There is no common theme to the product messaging they are creating, and their ability to reduce product setup costs has been hampered by these decisions.

In Summary: Product Data is Your Product Messaging

Micro moments and product experience management is just fancy terminology for what is simply an understanding of the importance of your product data. If your vision is to control your product messaging, you have to start with your product data. A PIM tool is the only functional approach that meets that goal, but has to be looked at as a foundational piece of that product messaging. Attempting to reduce product setup costs or speed product data transfer is a valid business goal and a justification for a PIM project, but the true visionary approach has to include an overall product messaging approach. Otherwise, your business is limiting the return on investment it will achieve from any attempt to solve your product data setup and distribution problems.

Dan O’Connor is a Product Taxonomy, Product Information Management (PIM), and Product Data Consultant and an avid blogger on taxonomy topics. He has developed taxonomies for major retails as well as manufacturers and distributors, and assists with the development of product data models for large and small companies. See his LinkedIn bio for more information.

I am afraid that Gartner does not help

“The average financial impact of poor data quality on organizations is $9.7 million per year.” This is a quote from Gartner, the analyst firm, used by them to promote their services in building a business case for data quality.

AverageWhile this quote rightfully emphasizes on that a lot of money is at stake, the quote itself holds a full load of data and information quality issues.

On the pedantic side, the use of the $ sign in international communication is problematic. The $ sign represents a lot of different currencies as CAD, AUD, HKD and of course also USD.

Then it is unclear on what basis this average is measured. Is it among the +200 million organizations in the Dun & Bradstreet Worldbase? Is it among organizations on a certain fortune list? In what year?

Even if you knew that this is an average in a given year for the likes of your organization, such an average would not help you justify allocation of resources for a data quality improvement quest in your organization.

I know the methodology provided by Gartner actually is designed to help you with specific return on investment for your organization. I also know from being involved in several business cases for data quality (as well as Master Data Management and data governance) that accurately stating how any one element of your data may affect your business is fiendishly difficult.

I am afraid that there is no magic around as told in the post Miracle Food for Thought.

The Rise of Business Ecosystems in Data Management

There are many signs showing that we are entering the age of business ecosystems. A recent example is an article from Digital McKinsey. This read worthy article is called Adopting an ecosystem view of business technology.

In here, the authors emphasizes on the need to adapt traditional IT functions to the opportunities and challenges of emerging technologies that embraces business ecosystems. I fully support that sentiment.

In my eyes, some of the emerging technologies we see are in large misunderstood as something meant for being behind the corporate walls. My favorite example is the data lake concept. I do not think a data lake will be an often seen success solely within a single company as explained in the post Data Lakes in Business Ecosystems.

The raise of technology for business ecosystems will also affect the data management roles we know today. For example, a data steward will be a lot more focused towards external data than before as elaborated in the post The Future of Data Stewardship.

Encompassing business ecosystems in data management is of course a huge challenge we have to face while most enterprises still have not reached an acceptable maturity when it comes internal data and information governance. However, letting the outside in will also help in getting data and information right as told in the post Data Sharing Is The Answer To A Single Version Of The Truth.

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Infonomics and Second Party Data

The term infonomics does not yet run unmarked through my English spellchecker, but there are some information available on Wikipedia about infonomics. Infonomics is closely related to the often-mentioned phrases in data management about seeing data / information as an asset.

Much of what I have read about infonomics and seeing data / information as an asset is related to what we call first party data. That is data that is stored and managed within your own company.

Some information is also available in relation to third party data. That is data we buy from external parties in order to validate, enrich or even replace our own first party data. An example is a recent paper from among others infonomic guru Doug Laney of Gartner (the analyst firm). This paper has a high value if you want to buy it as seen here.

Anyway, the relationship between data as an asset and the value of data is obvious when it comes to third party data, as we pay a given amount of money for data when acquiring third party data.

Second party data is data we exchange with our trading and other business partners. One example that has been close to me during the recent years is product information that follows exchange of goods in cross company supply chains. Here the value of the goods is increasingly depending on the quality (completeness and other data quality dimensions) of the product information that follows the goods.

In my eyes, we will see an increasing focus on infonomics when it comes to exchanging goods – and the related second party data – in the future. Two basic factors will be:

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We Need More Product Data Lake Ambassadors

ambassador

Product Data Lake is the new solution to sharing product information between trading partners. While we see many viable in-house solutions to Product Information Management (PIM), there is a need for a solution to exchange product information within cross company supply chains between manufacturers, distributors and retailers.

Completeness of product information is a huge issue for self-service sales approaches as seen in ecommerce. 81 % of e-shoppers will leave a webshop with lacking product information. The root cause of missing product information is often an ineffective cross company data supply chain, where exchange of product data is based on sending spreadsheets back and forth via email or based on biased solutions as PIM Supplier Portals.

However, due to the volume of product data, the velocity required to get data through and the variety of product data needed today, these solutions are in no way adequate or will work for everyone. Having a not working environment for cross company product data exchange is hindering true digital transformation at many organizations within trade.

As a Product Information Management professional or as a vendor company in this space, you can help manufacturers, distributors and retailers in being successful with product information completeness by becoming a Product Data Lake ambassador.

The Product Data Lake encompasses some of the most pressing issues in world-wide sharing of product data:

The first forward looking professionals and vendors in the Product Information Management realm have already joined. I would love to see you as well as our next ambassador.

Interested? Get in contact:

IT is not the opposite of the business, but a part of it

Yin and yangDuring my professional work and not at least when following the data management talk on social media I often stumble upon sayings as:

  • IT should not drive a CRM / MDM / PIM /  XXX project. The business should do that.
  • IT should not be responsible for data quality. The business should be that.

I disagree with that. Not that the business should not do and be those things. But because IT should be a part of the business.

I have personally always disliked the concept of dividing a company into IT and the business. It is a concept practically only used by the IT (and IT focused consulting) side. In my eyes, IT is part of the business just as much as marketing, sales, accounting and all the other departmental units.

With the raise of digitalization the distinction between IT and the business becomes absolutely ridiculous – not to say dangerous.

We need business minded IT people and IT savvy business people to drive digitilization and take responsibility of data quality.

Used abbreviations:

  • IT = Information Technology
  • CRM = Customer Relationship Management
  • MDM = Master Data Management
  • PIM = Product Information Management