Big Data : It Takes Three to Tango

I have noticed that little has been written about the set-up needed to succeed in Big Data projects.

To increase chances of successful implementation it is important to have the players well connected: Business, IT and Data Science.

Five steps to connect these three teams:

First it is key that Business, IT and Data Science teams understand the basics of each other’s language.  That is not a trivial challenge, considering that it is even hard for specialists to keep up with the lingo and developments in their own domain.

Secondly, instead of rushing towards solutions and road maps, sufficient time needs to be spend on : What is the real problem to solve?.

Thirdly, use-what-you-have. Look at the tool-set and capabilities you have in-house. In larger companies especially there are quite often sufficient tools available to make a first step. Look for the analytical brains in your teams. They might not have Data Science on their business cards, but they could have the potential.

Fourthly, go for the low-hanging fruit. For big data projects to be successful, it is essential to make many iterations. Find an area that jumps out, focus, keep scope limited, and start trying out.

Last but not least, mix and mingle. Don’t make this a project for one group, make it a joint initiative from day one. Try to have the team in one room to maximize learning, feedback and communication.

InfoGraphic DataPlough 2015 09 04 It Takes 3 To Tango

Big Data hype vs CRM hype – different but same mistakes?

Big Data and CRM on Hype Cycle

In the early part of this century I was involved in CRM implementations. Looking at the current surge in big data technologies I was wondering if there are similar things happening now as in the days when CRM was hot.

After doing more than a dozen CRM implementations I took some time to reflect on the challenges around CRM implementations.

Here is the list of reasons why CRM projects often fail:

  • No executive sponsorship and involvement
  • Unchanged organizational  structures  and culture
  • Leaving out the customer in defining CRM programs
  • Little attention to new customer metrics
  • Technology is leading the CRM program
  • Data quality issues
  • CRM only at departmental levels
  • Lack of CRM skill and resources

I added to that a quote from John McKean revealing a paradox in the competencies companies have invested over the years: “Over 90% of all CRM/Customer Information investments relate to technology and information. Less than 10% is historically invested in people, process, organization, culture and leadership” (John McKean. Information Masters, Secrets of the Customer Race, John Wiley & Sons, Ltd).

Although the scope and opportunities regarding Big Data are beyond that of CRM, same list of challenges apply.

I wonder how much we have learned from this….

Efficiently moving in the wrong direction

Most of those who visited a business school have been exposed to the market planning process.

It’s simple and straightforward, analyse the market, segment it, find the right spots and then target!

Simple steps, when followed through consciously, will make your endeavours effective.

Not per se efficient.

That’s something else.

And here is the issue.

It appears to me that in business there is an overemphasis on efficiency. How to operate faster, with sophisticated tools preferably. There is a strong focus on doing more tasks, and doing them in a shorter timeframe.

There are many examples to find. Look at sales. How does your funnel evolve? Is the size the right size? How many deals have you closed? How many visits did you do this week? How many calls did you do (today…)?

We generally do understand how to seperate out lead-measures from lag-measures.

But did we target the right set of customers? We might think we did. But the chances are that you’ve spend relative little time to analyse the customer reference data.

In many companies this process of segmentation and planning is done in a rush. Often using the ‘accountlist’ approach, rank revenue and deploy resources…

Just 1 example of how to go efficiently in the wrong direction.