Category Archives: Professional Services
In my previous post I discussed effective stakeholder management and communications as a key enabler of successful data quality delivery. In this blog, I will discuss the importance of demonstrated project management fundamentals.
Large-scale, complex enterprise Data Quality and Data Management efforts are characterized by numerous activities and tasks being performed iteratively by multiple resources, across multiple work streams, with high volume units of work (i.e. dozens of source systems and data objects, hundreds of tables, thousands of data elements, hundreds of thousands of data defects and millions of records). Without the means to effectively define, plan and manage these efforts, success is nearly impossible. (more…)
This week we had the privilege of participating in two significant conferences taking place in San Francisco. I was on a CMO panel at the B2B Digital Edge Live conference (#DELiveSF), while my colleague Daniel West presented at the Forrester Annual Enablement Forum (#tse12). I found it intriguing how both conferences focused on the same end-result … the “Customer”.
In some respects this is quite surprising given one normally associates Enablement with the process of training sales on how to sell, while marketing always talks about promoting thought leadership into the social network or generating leads from prospects. So why the change?
I think the answer here relates to how both disciplines are moving forward in this modern era driven by social networking. No longer is it just a one-way dialog between vendor and customer – you know, where the vendor promotes products & services via a web-site, or advertises in a magazine. It is now imperative that there is a two-way dialog. Customers are no longer silent! They talk, and they discuss – both good and bad. Vendors need to focus on ensuring their customers are successful. This means focusing on “listening” to their customers and understanding what total customer success means to them – whether it is online, in user groups, at events or in one-to-one meetings. Interestingly, this is one of the fundamental tenents of cloud computing through which service is paramount in order to drive repeatable subscription revenues.
Hence the focus of enablement must shift from simply training sales, and move to enabling sales to foster relationships with customers in order to deliver solutions that really deliver on key business imperatives. The entire value delivery chain (from first contact through to sale, implementation and ongoing success) must be aligned and working for customer success – because vendors are now visibly under the microscope and increasingly being compared and discussed in public. Several comments jumped out at me from the live conference twitter stream (#tse12):
- Certify sales people on talking to buyers, not talking about products.
- 86% of business buyers engage in web research independent of sales cycle.
- 8 months ago, enablement was nice to have, now it is recognized as a must have
- Sales Enablement = Make your customer a hero. That’s why I use “future advocate” and NOT “prospect”.
Strong words indeed which then align with the role of modern marketing teams – Engaging with customers through their chosen social networks to discuss their needs and help position solutions for their success. The role of marketing then becomes increasingly focused on finding the early stage researchers as they engage on social networks and leverage online assets. The role of marketing has now moved to that of engaging online, embracing customers and engaging in ongoing dialog. Again, several topics jumped out from the live conference twitter stream (#DELiveSF):
- Enable B2B salespeople to do what they do best, with digital at the core: data, content, mobile, social, CRM.
- B2B marketing: Start with audience design. Target the influencers of the influencers & create content in places they seek it.
- Marketing direction for digital: brands need to become publishers. Content is king!
- Digital Edge Live: Control social mess before it controls you.
That last point is key – a significant problem is that this modern world of online proactive marketing has become complicated. At the B2B Digital marketing conference, we were asked by the moderator, Kate Maddox, on what our greatest challenges were in digital marketing. Three topics that interested me:
- Joining the dots between out-bound email marketing with social media to nurture customers and prospects efficiently.
- The cultural change associated with evolving from an old-fashioned traditional organization to a leading social enterprise.
- Understanding where user groups now exist – on traditional web-sites – or beyond in the social network of linkedIn, Facebook and other networks.
Marketing and Enablement are evolving rapidly into adjacent displines linked with a common goal of embracing the customer and ensuring that the entire value delivery chain is focused on their success – because without their success we are simply fooling ourselves into believing we are building a sustainable and successful business model.
What do you think?
This article explores Agile Data Integration and Business Intelligence practices and contrasts leading practices and technologies. First some definitions.
Agile DI is the application of agile techniques (iterative/incremental development, cross-functional self-organizing teams, rapid/flexible response to change, etc.) to address data integration challenges such as migrating data between systems or consolidating data from multiple systems. Agile BI is the application of agile techniques to address business intelligence challenges such as identifying and analyzing data to support better business decision-making. These two disciplines sometimes overlap or support each other. For example, you might use Agile DI to move data into a data warehouse and Agile BI to get it out of the warehouse in a useful form. (more…)
Last week I wrote about the role of collaborative learning in achieving a transformation to Lean Value Streams. To make it more challenging and take it to the next level, let’s assume that all the people involved in the learning scenario all work for the same company, but they are in different functional groups and may never work together as a team again. In other words, how can the lessons learned by the integration project team be communicated to other project teams? How can we make organizational learning sustainable? (more…)
As a routine matter of delivering care, billing for services and operating their hospitals and physician practices, healthcare providers deal with patient’s protected health information all day, every day. Dealing with the data becomes routine and it’s easy for sometimes onerous security and privacy policies and procedures to be overlooked. While we’d all like that not to be the case, delivering healthcare (and getting paid for it) is a hugely complex undertaking and focusing exclusively on human processes and calling for constant vigilance and attention to detail can only go so far. (more…)
Lean management practices have been applied in recent years to virtually all business functions and processes, including of course Lean Integration. IT architecture is no exception. But what exactly does a Lean Architecture look like and how could you measure its “leanness”? Since there is no generally accepted definition lean architecture, and since I won’t bore you with mine, it might be easier to describe what a non-lean architecture looks like. Or to ask it differently, what are some non-lean approaches to architecture? (more…)
In March of last year I posted a blog here entitled: The Achilles Heel Of Cloud Computing – Data Integration. “In fact, what currently limits the number of cloud deployments is the lack of a clear understanding of data integration in the context of cloud computing. This is a rather easy problem to solve, but it’s often an afterthought.”
So more than a year later, where are we?
While some progress has been made, many cloud computing implementation projects continue to ignore the value of a sound data integration strategy and the use of the right data integration technology. Most paint themselves into a data quality and data synchronization corner, but give them time. (more…)
The CIO of GT Inc. (the fictitious name of a real company) met with his middleware vendor rep to deliver some depressing news.
“We established an outsourced factory delivery model two years ago using the productivity tools that you sold us and we made it our enterprise standard. The factory results however, are discouraging use of your integration platform. Projects are not getting approved by the business because of high costs, or else project teams are working around the standard and building hand-coded solutions. Did I make a mistake in buying your software?” (more…)
Why does one software project cost twice as much as another? Is it because it is developing twice as much functionality as the other? If you contract with two system integrators, how can you tell which one is more productive? In a multi-year outsourcing arrangement, is your supplier getting more or less efficient year over year?
An enduring challenge in the software industry is establishing a standard unit of measurement that expresses the amount of business functionality in a given information system so that questions like these can be addressed. Most organizations have not adopted a formal measure, but of those that have, the most widely accepted measure is function points which were defined by Allan Albrecht in 1979. But are function points an effective metric for integration projects? (more…)
Informatica has been involved in many high value application consolidation projects and naturally our perspective is all about the data – we are interested in its quality, its lineage, its size and shape and how it correlates from one application to another. We provide a range of services to help our customers with this. This is all very important but we also need to think about the larger picture: the application servers, the database servers, shared infrastructure and storage.
Automated [IT infrastructure] discovery is a kind of holy grail – the idea is that you detect all of the servers and inter-server communications happening within a data centre, and somehow you can auto-magically infer business applications and services and all their dependencies. As is so often the case the reality is somewhat more complex – what you actually need to do is then apply lots of filters and human refinements to remove a vast amount of noise so that you end up with a useful and usable model.