Archives For Analytics Culture

2015: The Year of Data Leadership

October 30, 2015 — Leave a comment

Preface:

During November’s Data Leadership Conference in London I will be updating the audience on the progress to date that we have made during 2015: The Year of Data Leadership. I promise to share those findings in a subsequent posting shortly after the conference. In the meantime, this is the premise that started the thought process I used:

“The strategic value of Big Data & Analytics can only be realized when they are fully leveraged and exploited by the entire Enterprise. Top Down Data Leadership is essential to the success of these endeavors.”

Body:

As the focus of industry hype moves from Big Data to the Internet of Things we have a unique opportunity to turn our attention to one of the underlying disablers of broad success in using data & analytics to their full potential in any Organization; the lack of Top Down Data Leadership.  During the past couple of years we have seen a fever pitch in Organizations’ anointing proxies to the status of superheroes in respect to Data & Analytics Officers. While there have been many such appointments, most are now being scrutinized as the widening gulf between the rhetoric and reality becomes more apparent. This effort to create “Chief Whatever Officers” has been foolhardy in my opinion, as it has completely dodges the need for the Board and CEO to become directly accountable for the Organizations management and exploitation of data and their leverage of analytics across the enterprise to create a “culture of evidence-based decision making”. My aim in 2015 is to change this dynamic.

In 2015, I would like to create much more than awareness of this underlying challenge, but to make actionable its solution in what I am calling “The Year of Data Leadership”. In the Year of Data Leadership I would like every CEO and their Board (Public, Private, NGO, Not-for-Profit, etc.) to accept the fact that they (and Not IT) are fully accountable for “all things data and analytics”. I want them to embrace this accountability and make it core to their Strategies and Operational Plans. I am challenging them to step up to this leadership mantle and provide the Organization with a plan of action to put it on a trajectory to becoming a “Predictive Enterprise” within 5 years (2020). This Decision Making transformation would move them from being gut-based decision (relying on experience and anecdotes) making Organization to one where evidence (facts, decision science and the appropriate amount of intuition) guide all decisions at every level.

This is an ambitious undertaking for even the most agile of Organizations, but a necessary one if the competitive advantages of a Predictive Enterprise are ever going to be realized. To accomplish such a Transformation I strongly recommend approaching it as follows;

1.- Immerse the CEO, Board & Senior Executive Team in a series of Boot camps designed to immediately (and measurably) raise their acumen and competencies in the domains of Decision Science & Analytics, for “you cannot lead what you don’t understand”.

2.- Make Data, Information & Analytics Core Competencies in your strategic and operational endeavors. Make then pervasive and break down silos and centers of excellence to make capabilities mainstream and ubiquitous to all aspects of your operational domain. This will require investment in staff development and in the early stages may require shadowing of staff with outside experts, mentors and coaches.

3.- Manifest Cultural Adoption by all members of the Organization of this new strategic paradigm i.e. Becoming a Predictive Enterprise. Organizational Culture is “the shadow of the CEO, Board and Senior Executive Team”. It is found in every corridor and behind every door across the enterprise and is molded from the Top-down. To begin to change a culture requires Top Down Leadership to changes it behavior and modify all cultural norms and activities. The entire Leadership team must engage with the Organization directly (with support by Change professionals) to lead by example in regards to championing the new direction and its virtues.

This three-pronged approach will produce the maximum results in the shortest period of time and requires close coordination, substantial investment of time and resources to succeed. It is truly transformational and should not be a sub-priority to other Enterprise-wide strategic and operational initiatives.

The Nexus of Top-Down Leadership, Cultural Adoption and the enabling Core Competencies of Data, Information & Analytics creates a unique strategic framework for becoming a Predictive Enterprise. All components are required to work in concert to achieve a true transformational outcome within any Organization who wants to fully exploit data & analytics for competitive advantage.

*-This posting in an edited version appeared in the January 2015 issue of Information Age (UK)

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“Every type of data needs Data Leadership”*

October 13, 2015 — Leave a comment

As we all begin to make our final plans to attend Data Leadership 2015 late in November (http://bit.ly/1YOKrJV), it struck me after reviewing the agenda once again that we have now reached a point where there are now many discrete & different forms of data being used across most enterprises (Public, Private & NFP) on a regular basis. Much of this data now comes from outside the Organization in the form of Open Data, Reference Data, Social Media Data, etc.  All of these data sources are managed to varying SLA’s and Best Practices in respect to quality, veracity, latency, etc., making them extremely suspect at times in my opinion. However, most Enterprises do not question their sources of this external data and simply embrace it for the “Richness” that it provides without consideration of the care & feeding that it has undergone over its lifetime. Why is there such implicit trust here one might ask especially in light of most Organizations’ challenges with their own data in respect to quality, etc.?

The notion of Data Leadership is one where Data, Information & Analytics are treated as core competencies by every organization. As such, they are strategic in their nature and are major leverage points for the Organization to use in creating Competitive Advantage. These core competencies rely on the fact that the data that underpins them is of the highest quality regardless of metric used to evaluate them with. This requirement transcends all industry segments and applies to Government and NGA’s alike. Bad or misleading data in respect to accuracy impacts everyone in a debilitating way. Given this, every Senior Executive has a Data Leadership accountability to make sure that the highest quality standards are maintained, even if the data is sourced from a 3rd party or from the Open Data Community. Herein lies the rub. How do you manage what you don’t control?

As data is monetized and sold by the pound by Reference Data providers,  much less as it is freed up from the government silos that it has been hoarded in for decades by the Open Data Community, it must be made “fit for purpose” and undergo rigorous conditioning to insure that it is “in shape” for consumption regardless of the use case. This is not the case today with the vast majority of what I call 3rd Party Data, most specifically what is sourced from the Open Data portals that now proliferate the landscape. Reference Data & Social Media data are better managed over their lifecycles because there was always a profit motive behind its creation, but it still has its challenges. I will leave that discussion to a future article. For now, let’s focus on the Open Data world.

Open Data now comes from both Government entities (and NGO’s) as well as Commercial interests. Both use these data sets internally to run their Organization and then “hive off” some (or all) of it for sharing with the Open Data Community. In most if not all cases, it is done as a side activity (begrudgingly) by the IT Staff who are always hard pressed to have enough staff, time & other resources to do their “day jobs”. This creates a dynamic that does not foster high quality data in any regard. To overcome this, we must have Data Leadership by those Executives who are accountable for delivering data products to the Open Data Community. They must insure that all data under their watch is representative of what would be acceptable internally by the Org, much less to a higher standard if possible.

We still live in a “Garbage In, Garbage Out” world. You cannot have successful (or believable) Analytics Outcomes without good data as foundation. Forget about creating Competitive Advantage if everyone continues to waste all their cycles on fixing bad data or questioning the source of their truths.

As there will be representatives from both the providers and the users of these 3rd Party data sources at DL 2015, I wanted to impart one basic message to all who are planning on attending; “Every type of data needs Data Leadership”.

As a community of data & analytics professionals we must insist that all data must be guided by some basic Governance principles that affect the useful lifecycle of the data assets that are being created and consumed. I look forward to discussing all of this further with everyone at Data Leadership 2015.

*This article appears in an edited form in the October 2015 issue of Information Age (http://bit.ly/1RCgB6p).

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Profiles in Data Leadership (Update)

September 14, 2015 — Leave a comment

It’s been a while since my last update on the Eight CEO Leaders featured in my series; “Profiles in Data Leadership”. I am actively working on a presentation for this Fall’s “Data Leadership 2015” conference in London where I will discuss each one of these data leaders in the context of “2015 – The Year of Data Leadership” (that’s a lot of references to Data Leadership isn’t it?).

I thought that I would provide a taste of what will be discussed in November through these 3 short overviews. Hope you enjoy it.

Cheers,

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In Big Data, Business Analytics, Business Transformation, Chief Data Officer, Information Management, Leadership , , , , , ,
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PASSBAC Presentation on The Data Leadership Nexus & Profiles in DataLeadership (3)

May 6, 2015 — Leave a comment

As it has been some time since I posted on The Data Leadership Nexus and Profiles in Data Leadership I thought that I would share with my followers the presentation on these topics that I recently made at the PASS Business Analytics Conference in Santa Clara, CA.

You can view the presentation on SlideShare via the following Link:  http://www.slideshare.net/RXLee1/bac2015-richard-leedataleadershipnexusf

Notes are included on the side as you view the presentation.

Enjoy!

Richard

In Business Analytics, Business Transformation, Information Management, Leadership , , , , ,
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Business Analytics and the Mid-Market (Part 4 of 4)- “Choosing your Business Analytics Strategic Partner”

February 21, 2012 — Leave a comment

In conjunction with a webinar that I am participating in on 2/29 ( ZD & IBM – “Get More from your Data: How Business Analytics Gives You a Competitive Advantage”), I am  posting  a series of four blogs entitled “Business Analytics and the Mid-Market“.

(To attend my webinar on 2/29, Register at: http://b2b.ziffdavis.com/webcasts/improve-performance-your-data-business-analytics/?tfso=10480 )

This is Final installment (No. 4).in that series; ”

To recap from my previous 3 postings;

  • Business Analytics (BA) is “the use of data & analysis techniques to understand your business in a a way that facilitates better decision making”. BA is “fact-based decision-making in real-time based upon a 360 degree view of the business. It portends to offer the highest potential for competitive advantage of any strategic enabler (much less tactical or operational) available in the business leaders portfolio today, much less the future.
  • To achieve true Competitive Advantage (CA) one must embrace the notion of Business Analytics  in a holistic fashion in order to create “a pervasive culture of analysis and numerical literacy”. The 5 components of a holistic approach are; People, Processes, Technology, Culture & Data
  • To achieve competitive advantage (via differentiation), much less sustain it, Organizations must make Business Analytics a core competency and foster its deep usage across all domains of the business. Business Analytics must be made pervasive across the organization
  • Critical to the successful creation of Competitive Advantage is the role of the Business Analytics Strategy. It should encompass all domains of your business and support the 5 Pillars (People, Processes, Technology, Culture & Data) of a holistic approach to Business Analytics.
  • A successful Business Analytics Strategy (BAS) is one that is fully-aligned and synergistic with the Organizations’ Long-Term Strategy (3-5 years) and companion Near-Term Strategic Goals & Outcomes (1-2 years).
  • The key to developing your Business Analytics Strategy is to find the entry and inflection points in your strategy’s execution where BA can be embedded and used as either a catalyst or an accelerator for success.
  • The value of having an Analytics Partner (AP) in this process is substantial and in the early stages of any organizations’ journey to Analytics Maturity they can make the difference between success and disappointment, much less outright failure.

“Choosing an Analytics Trusted Advisor to support your BA Strategic Planning Process”

At this point we have established that pervasive Business Analytics (BA) can be a game changer for every Organization. To achieve Competitive Advantage (CA) from Business Analytics you need a well defined Strategy that aligns all BA activities and outcomes with the Business Goals & Objectives (BG&O) defined in both the long-term and near-term strategies & tactics of the Organization. This alignment should be across all major domains of the Business/Organization. Fostering and leveraging synergies found in core information assets into Analytical Focus Areas that benefit the entire organization is the cornerstone of such a Business Analytics Strategy.

Developing a BAS requires collaboration and partnership with an Analytics Trusted Advisor in the vast majority of cases. Most organizations in the Mid-Market do not have the depth of personnel or base of applied experience required to create a comprehensive Business Analytics Strategy internally. Staff efforts are mainly focused on Operational Performance and Innovation Activities and not on strategy endeavors, therefore justifying the need for a Trusted Advisor as being paramount to success. Choosing a BA Trusted Advisor is an early step in your Analytics Journey (AJ) and should be done after a thorough and rigorous interview & selection process. There are many Business Intelligence consultancies who claim to be as good at Business Analytics, but one should be wary of such claims. Although the worlds of Information Management (IM), Business Intelligence (BI) and Business Analytics are merging together at many levels, the expertise required to develop a successful Business Analytics Strategy  is limited to a small community of Consultancies and Suppliers. In most cases you will have to take a long-term view of the partner whom you choose in the context of not only helping you to develop your BA Strategy, but ultimately helping you to acquire & deploy the necessary solutions & capabilities required to insure that the strategic outcomes successfully achieved. The Business Analytics Trusted Advisor will provide support in developing, testing and optimizing early Analytical Models & Data Sets. All of these activities will be complimented with an effective plan & activity set for Change Management & Cultural Adoption for your Organization. A holistic approach to your overall Business Analytics Strategy and its successful execution requires a long-term view of achieving success and the support of Trusted Advisor whom can provide all of these types of services to the levels required.

Choosing your Analytics Trusted Advisor does not need to be an arduous process. It could be as simple as engaging with an existing partner or conducting a quick survey of the leaders in the Business Analytics space who have focus areas on your type of business (Mid-Market) and industry segment (Service Providers, Software/Technology, Retail, etc.). The market leaders will all have consulting teams & solution sets optimized for the specifics of your size & type, as well as having a deep portfolio of  critical enablers for Business Analytics success e.g Strategy Templates, Specific Analytics Solution sets (Customer, Finance, Corporate Performance, etc.), Change Management collateral, Information Governance guidelines, etc. All of these elements will be required over the long haul as you move from Strategy to Execution t0 Outcomes. Additionally, your BA Trusted Advisor will bring an overall discipline to the overall approach by helping you to focus on early quick wins in your Analytics Journey, as you change your culture to being an Analytics-Driven one over time. The depth and maturity of your BA Trusted Advisors appraoch to achieving such outcomes while reducing risk to a manageable level is a Critical Success Factor that every organization should look from in their partner(s).

In the end, each Organization must define the criteria and process for choosing and engaging with an Analytics Trusted Advisor. Going it alone is fraught with risks and should only be advocated if the Organization believes that it has the depth of experience and know-how to achieve Analytics Success on their own. In choosing your Advisor one must look for a leader who has made/demonstrated a commitment to supporting Organizations of your size, ambitions and market focus. Only a handful of Consultancies/Suppliers in the marketplace rise to this level of distinction.

For more information on one such Trusted Advisor in the market (IBM), please check out the following links;

http://www-01.ibm.com/software/analytics/excellence-center/

http://www-935.ibm.com/services/us/gbs/bao/

http://www-935.ibm.com/services/us/gbs/thoughtleadership/ibv-embedding-analytics.html

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