Horatio Nelson, Dwight Eisenhower, SharePoint, and Big Data
John Mancini’s What does the future hold for SharePoint will resonate with anyone who has ever managed a corporate SharePoint implementation. Mancini points out that many such implementations stumble not because of technological limitations but because of a lack of management buy-in and ineffective or limited attention to business process change management.
I see a lot of truth in what Mancini says, even when I.T. is handling it all. There are many challenges associated with SharePoint adoption that I.T. can’t solve on its own, especially when there are expectations that users will quickly start using SharePoint to collaborate and share information. There’s a lot more to collaboration than just providing a technology platform.
Here I’m interested in how learning from SharePoint adoption challenges might be relevant to the adoption of improved data analytics by organizations eager to take advantage of the modeling, visualization, and analytical capabilities of today’s crop of “big data” and related tools.
Some organizations will be well prepared to make use of such tools especially those for which data and data analytics are already accepted as standard operating procedures. For others, significant challenges might exist due to the novelty of the new tools or to the uncertainties raised by how to take advantage of the potential information “gold” contained in expanding volumes of structured and unstructured data.
Change is difficult. As managers of SharePoint adoption have learned, the challenges may have more to do with personal behavior habits then with uncertainty concerning how to use the technologies. Overcoming resistance to the use of new analytical tools requires both careful planning as well as a hands-on demonstration of value. Planning is needed especially in terms of stakeholder involvement and management expectations. Rapid execution and delivery of useful results quickly builds trust and a foundation for future strategic changes in how data are managed and analyzed. Where do you start if your organization isn’t already data-centric?
That’s one of the questions I’m pondering now. I’m sympathetic to the immortal words of Admiral Horatio Nelson:
“Never mind about maneuvers, go straight at ‘em!”
I don’t think Lord Nelson was recommending against planning. He was recommending action when faced with an opportunity whether events were unfolding according to plan or not.
Nelson would probably also agree with what Dwight Eisenhower said:
“In preparing for battle I have always found that plans are useless, but planning is indispensable.”
As I’ve suggested elsewhere it’s best to combine planning with action:
- Planning to make sure the right connections are made within the organization and the important problems are being targeted.
- Action via a prototype or demonstration project to gain hands-on experience with the data and to build a sound solid foundation for growth.
If your point is to improve collaboration, understanding the potential for receptivity and understanding among target staff will be important. People unaccustomed to sharing documents and other types of media might resist the discipline that a SharePoint implementation calls for, just as people unaccustomed to using data in other than basic spreadsheet form might resist changing.
Either way, both planning and execution will be required both an understanding of the underlying technology and analytical issues as well as support for making connections between data and the organization’s requirements.
One further requirement will be for agility and nimbleness. Recognizing “targets of opportunity” and then responding quickly without excessive oversight or bureaucracy will be key, especially in situations where data analysis requires an exploratory phase. It is the nature of exploration that one can’t always predict what you’ll find when you wade into the data.
This is where a shared understanding of goals and objectives is essential, especially an understanding of the strategic importance of the process or decision that’s being targeted by improved analytics.