Social media have penetrated our lives. We share ideas, experiences, thought, complaints, and compliments with everybody. At the same time we see quite some controversy concerning the  privacy policies of companies such as Facebook and Twitter. Some people even think that European privacy regulation does not apply to them, as they are US-based companies. 

In our research project “New Models for the Social Enterprise” privacy regulation was one of the topics we tackled. The good news is that we as consumers outside the US are still governed by EU regulation and national policies. If a Dutch company, for example, uses data from Twitter to analyze what is mentioned concerning their brand, the mood etc., Dutch laws apply (the Wet Bescherming Persoonsgegevens). The data collecteda and analysed  by social media mining companies, such as Coosto, falls under the jurisdiction of country they work. If a company uses or stores Tweets, Facebook messages etc., they are data processors themselves. This does not hold for the use or storage of aggregated data that cannot be linked to individual users (which is not the same as anonymised data; data hardly ever is anonymous if collected in larger quantities…).

Mail exchange between companies and customers, or mail in general, is private. This brought the question to my mind whether or not direct messages in, for example, Twitter, are really private or not? In the example data we had from Twitter, direct messages did not appear, but this could be coincidental. The privacy rules of Twitter  do not mention direct messages.

In order to get clarification, we simply asked Twitter (privacy@twitter.com), on April 24th:

Dear sir, madam, 

I have been a frequent and enthusiastic user of Twitter, and will be so in the years to come, I expect. However, I do have a question concerning privacy. Everything I tweet is open to the public, and tweets are brought together and sold for business purposes to companies etc. So much is clear.

Direct messages, however, give the feeling of being private, similar to e-mail messages. From your privacy statement I cannot derive whether of not DMs are treated differently than normal tweets. I.e., are they also analyzed, aggregated and/or sold to third parties? 

 Kind regards,

@WilJanssen

It took a while and some friendly reminders, but in the end, I received an answer:

Encouraging, to say the least. Everything in a DM remains within Twitter and is not shared or sold. Maybe the answer above is not a legally correct answer, but still, it is clear. The use of DM’s is common in webcare, but should be used wisely. It is more effective to make sure the mail addresses of customers are known and correct and to use mail for information that is personal or private. Mail is an effective means for communication, easy to store and archive, and legally binding. Social media have a role in a swift and informal discussion. Use it wisely in a business relation.

Wil Janssen is managing director of InnoValor and guest author for our blog. InnoValor and BiZZdesign are research partners in the ‘New Models for the Social Enterprise’ project.

In part 1 of my blog I discussed how to select a CMDB and how to identifying the ITIL process to focus on first. Now that you have selected the tool and identified the process to start with, it’s time to start planning for the actual deployment. 
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“Data” is a big topic for many organizations. It may not come as a surprise that a lot is being said and written about using / securing / managing data. From a technical perspective, topics that are increasingly popular are big data, open data, and linked data, frequently in conjunction with security management, privacy, and business impact. More and more business forums also write about data.

Here are some highlights from last week’s news in the Netherlands (most of these are in Dutch):

• Telegraaf: Middelgrote bedrijven zien heil in ‘big data’

• Managers online: Organisaties staan te springen om Big Data, BI en Analytics binnen CRM

• Nu.nl: Nederlandse wetenschappers teleporteren voor het eerste data

• Marketingfacts: Hoe big data bol.com elke dag een stukje persoonlijker maakt

What is interesting about these articles is the fact that the focus seems to shift away from the traditional ‘systems thinking’ and towards data and business impact. This seems to fit well with the growing realization that “systems are temporary, but data is forever”. Take for example the articles about Customer Relationship Management (CRM). Over the last few years, many organizations have updated their CRM capability – including systems and processes – many times. A switch in systems typically means migrating data, something that is often seen as a one of the (technically) most challenging aspects of a system upgrade due to a change in standards, definitions, data structures and so on.

Data issues, benefits of managing data as an asset

The good news is that this hard work typically has big benefits: many issues with data quality become visible during (or: shortly after) migration. Perhaps the following sounds familiar:

• Records about key entities (such as customer, or product) are incomplete. There may be missing data about key attributes so the new system will not accept these records. Where does the missing data come from?

• We find out that data is incorrect: there is a mismatch between what we think is true according to the data, and what can be observed in reality.

• Data may be inconsistent: we have multiple records (which are potentially inconsistent) about our customers. Why is this the case? Can we reconcile these records? How does that affect different groups in our organization, such as Marketing, Sales, Finance, or the delivery organization?

   

• We are once more faced with the challenge that we have different definitions of key concepts. For example, Marketing and Finance have a different definition of “Customer”. Therefore, when management compares reports about Customer from these two functions, there have always been inconsistencies (which may or may not have been ‘fixed’ with all sorts of local solutions based on extensive use of spreadsheets).We now have to buckle up and come to a standardized definition, or choose to re-develop or local solutions…

The list goes on and on. the good news, though, is the increased attention for managing data as an asset. John Ladley frames it nicely. Data is ‘the new oil’ for many organizations. Like oil, data can be dangerous. If you don’t manage it properly then it may explode.

Maturity

Over the last few months we have conducted many interviews with organizations around data management, and maturity of the data management capability. We have developed a “data management maturity scan” which is based on the DAMA DMBOK. This experience confirms the trend that we have just identified: there is a trend to take data management seriously and invest in the maturity of the data management capability. Some key findings:

• Several organizations report that ‘culture’ is a key aspect in being successful with data. If the culture is all about systems (in Dutch: “probleempje systeempje” – which loosely translate to “build a new system for each problem”) then nothing will change.

• We see some organizations take a “technology route” to solving data issues: start with tooling around meta data, data quality management etcetera, and “experiment” in projects to see what can be achieved. This is a minority.

• More and more organizations focus on outcomes: what do we want to get out of our data? What do we need to make that happen? Based on goals and principles, sound investments in the data management capability can be made.

• Handling (large volumes of) unstructured (and highly volatile) data has a lot of potential. However, most organizations recognize that this requires a more advanced capability than handling structured (“rows and columns”) data.

• Ignoring some notable exceptions from recent engagements with one client, many organizations are starting to recognize the value of business-focused models of the data landscape: yes, it requires an investment, but the resulting models are almost a condition cine qua non for data management

Food for thought

So what does all this mean for you / your organization? As in so many domains, there is no silver bullet that will magically solve all your data problems. There is no cookie cutter approach: there are no answers, only (more and more) questions. Therefore, we offer some “food for thought”, some questions to answer in the context of your organization. First of all: have a look at your change portfolio, and focus on IT. How many of the upcoming projects are around “fixes”, around “stuff that has gone wrong with data” that we are now trying to fix? If you have figured this out, ask yourself the follow-up question: who is my go-to guy for data? Do I trust IT enough to fix my data issues, or should this be done by a data steward who truly understands the business?

Try to create a simple business case: do a quick “back of the napkin” assessment of how many hours per week a typical employee is busy with data issues (searching for missing data, fixing broken data, reconciling duplicate and inconsistent data, etcetera). Multiply this by the number of staff and an average salary to get a sense of how much bad data is costing you.

Focusing more on benefits: do you know which business entities are crucial for running day to day business? Also, does management have a solid understanding of processes, associated KPI’s, and the reports / dashboards / scorecards that go with it? Suppose we need new (BI-related) insights, how quickly can we typically deliver? Can we also show (i.e., in case of an audit) that we’re in control with respect to managing this data as a crucial business asset? Or would someone get really nervous when that question is asked…?

Of course we’ll gladly assist you in assessing where you are with respect to data. Our two-day course in Enterprise Data Management can, combined with a data management maturity assessment, be a great kick-start for getting the most out of your data!